Rechenkraft.net e.V. - Elektronische Bibliothek: e-Library

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Diese kontinuierlich aktualisierte elektronische Bibliothek stellt Fachliteratur zur Verfügung, die entweder direkt von den Betreibern einzelner DC-Projekte veröffentlicht wurde oder aber sich auf deren Arbeiten bezieht, bzw. als Grundlage für diese Projekte dient oder Methoden dieser Projekte einsetzt, erweitert, bzw. überprüft. Die angegebenen URLs sind sämtlichst getestet und verweisen direkt auf das zugehörige PDF-Dokument der Originalpublikation beim Originalverleger. Copyrightverletzungen sind somit ausgeschlossen. Es kann durchaus sein, dass einzelne Artikel nicht für Jedermann durch einfaches Klicken auf die hier angegebenen URLs zugänglich sind. Dies liegt dann an Copyright-bedingten Einschränkungen, die der jeweilige Verleger zu verantworten hat. Die Artikel sind dann aber normalerweise von Computern aus Universitätsbibliotheken herunterladbar oder können - oft allerdings nur in einer rudimentär formatierten Vorversion - auf den Webseiten der jeweiligen DC-Projektbetreiber gefunden werden.

Natürlich ist unsere Literatur-Zusammenstellung nicht vollständig und wird es angesichts der rasanten Entwicklung der einzelnen Fachgebiete wohl auch nie sein können. Nichtsdestotrotz gehen wir davon aus, dass es zumindest im deutschen Sprachraum - vermutlich sogar weltweit - schon jetzt die umfangreichste Sammlung ihrer Art ist. Die Artikel sind chronologisch geordnet, wobei die frühesten Publikationen oben, die neuesten unten stehen. Auf diese Weise lässt sich auch ganz gut die Weiterentwicklung des Projekts verfolgen.

Neben unserer eigenen eBibliothek zum Thema BOINC gibt es auch in Berkely eine.

BOINC Italy hat inzwischen ebenfalls eine kleine Übersicht zusammengetragen, die sich hier findet.

Auch auf dieser NCODED-Seite werden Publikationen von Distributed Computing Projekten zusammengetragen.

Folding@home bietet eine eigene Publikationsübersicht an.

Tools zur Verwaltung wissenschaftlicher Publikationen, die wir gelegentlich verwenden (einige kostenlose Dienste): JabRef, Zotero

Die Symbole und hinter einer Publikation weisen auf einen freien Zugang zur kompletten Veröffentlichung hin. Über ist i.d.R. das gesamte PDF verlinkt und führt zu einem Download dessen.

Populärwissenschaftliche Artikel zum Thema Distributed Computing

Alois Pumhösel, 21. August 2013, 19:24 in der Standard.at: Die Masse macht's

Rechenkraft.net

Seshadri A, Dubey B, Weber MHW, Varshney U. (2009). Impact of rRNA methylations on ribosome recycling and fidelity of initiation in Escherichia coli. Mol Microbiol. 72(3):785-808. doi:PDF.

Arora S, Bhamidimarri SP, Bhattacharyya M, Govindan A, Weber MHW, Vishveshwara S, Varshney U. (2013). Distinctive contributions of the ribosomal P-site elements m2G966, m5C967 and the C-terminal tail of the S9 protein in the fidelity of initiation of translation in Escherichia coli. Nucleic Acids Res. 2013 May;41(9):4963-75. doi: 10.1093/nar/gkt175. Epub 2013 Mar 25. PDF.

Arora S, Bhamidimarri SP, Weber MHW, Varshney U (2013). Role of the Ribosomal P-Site Elements of m2G966, m5C967, and the S9 C-Terminal Tail in Maintenance of the Reading Frame during Translational Elongation in Escherichia coli. J Bacteriol. 2013 Aug;195(16):3524-30. doi: 10.1128/JB.00455-13. Epub 2013 May 31. PDF

Gahrn-Andersen, R, Prinz, R (2021). How cyborgs transcend Maturana’s concept of languaging: A (bio)engineering perspective on information processing and embodied cognition. Rivista Italiana di Filosofia del Linguaggio, 15(2), 104-120. PDF.

Möller, S, Dreihsig, C, Hilgenhof, S, Willert, M. (2021) Crypto-Mining-Rigs als erschwingliche Hardware für wissenschaftliches Rechnen. Linux-Magazin, 03/2021. HTML.

Prinz, R (2022). A simple measure for biocomplexity. Biosystems, Jul;217:104670. PDF.

Prinz, R (2022). The modularity codes. Biosystems, Sep;219:104735. PDF.

Gahrn-Andersen, R, Prinz, R (2023). Ensuring wholeness: Using code biology to overcome the autonomy-heteronomy divide. Biosystems, March 2023, 104874. PDF.

Prinz, R (2023). Nothing in evolution makes sense except in the light of code biology. BioSystems, Volume 229, May 2023, 104907. PDF.

Prinz, R. (2023). Biological Codes: A Field Guide for Code Hunters. Biol Theory, 18:3, 26 July 2023. PDF.

Prinz, R (2024). How Agents Use Biological Codes and Artifacts to Interpret their Innenwelt and make Sense of their Mitwelt. Biosemiotics, 25 April 2024. PDF

Moreira Bernardo P., Gava Sandra G., Haeberlein Simone, Gueye Sophie, Santos Ester S. S., Weber Michael H. W., Abramyan Tigran M., Grevelding Christoph G., Mourão Marina M., Falcone Franco H. (2024). Identification of potent schistosomicidal compounds predicted as type II-kinase inhibitors against Schistosoma mansoni c-Jun N-terminal kinase SMJNK. Front. Parasitol., 26 April 2024. PDF.

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Asteroids@home

Josef Durech, Josef Hanus, Victor Ali-Lagoa (2018). Asteroid models reconstructed from the Lowell Photometric Database and WISE data. arXiv:1807.02083 [astro-ph.EP], doi: 10.1051/0004-6361/201833437

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BRaTS@Home

Coss, D. (2008). Simulation of Gravitational Lensing. NASA Missouri Space Grant Consortium. Retrieved from http://research.davecoss.com/nasa_mo_paper.pdf

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Climate Prediction (CPDN)

Ackerley, D., Highwood, E. J., & Frame, D. J. (2009). Quantifying the effects of perturbing the physics of an interactive sulfur scheme using an ensemble of GCMs on the climateprediction.net platform. Journal of Geophysical Research, 114(D1). doi:10.1029/2008JD010532

Collins, M. (2007). Ensembles and Probabilities: a New Era in the Prediction of Climate Change. Philosophical Transactions of the Royal Society A, 365(1857), 1957-1970. doi:10.1098/rsta.2007.2068

Fowler, H. J., Cooley, D., Sain, S. R., & Thurston, M. (2010). Detecting Change in UK Extreme Precipitation Using Results from the Climateprediction.Net BBC Climate Change Experiment. Extremes, 13(2), 241-267. doi:10.1007/s10687-010-0101-y

Frame, D. J., Aina, T., Christensen, C., Faull, N. E., Knight, S. H. E., Piani, C., Rosier, S. M., et al. (2009). The Climateprediction.Net BBC Climate Change Experiment: Design of the Coupled Model Ensemble. Philosophical Transactions of the Royal Society A, 367(1890), 855-870. doi:10.1098/rsta.2008.0240

Frame, D. J., Booth, B. B. B., Kettleborough, J. A., Stainforth, D. A., Gregory, J. M., Collins, M., & Allen, M. R. (2005). Constraining Climate Forecasts: The Role of Prior Assumptions. Geophysical Research Letters, 32(9). doi:10.1029/2004GL022241

Frame, D. J., Faull, N. E., Joshi, M. M., & Allen, M. R. (2007). Probabilistic Climate Forecasts and Inductive Problems. Philosophical Transactions of the Royal Society A, 365(1857), 1971-1992. doi:10.1098/rsta.2007.2069

Knight, C. G., Knight, S. H. E., Massey, N., Aina, T., Christensen, C., Frame, D. J., Kettleborough, J. A., et al. (2007). Association of Parameter, Software, and Hardware Variation with Large-Scale Behavior Across 57,000 Climate Models. Proceedings of the National Academy of Sciences of the United States of America, 104(30), 12259-12264. doi:10.1073/pnas.0608144104

Min, S.-K., Zhang, X., Zwiers, F. W., & Hegerl, G. C. (2011). Human Contribution to More-Intense Precipitation Extremes. Nature, 470(7334), 378-381. doi:10.1038/nature09763

Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., & Stainforth, D. A. (2004). Quantification of Modelling Uncertainties in a Large Ensemble of Climate Change Simulations. Nature, 430(7001), 768-772. doi:10.1038/nature02771

Pall, P., Aina, T., Stone, D. A., Stott, P. A., Nozawa, T., Hilberts, A. G. J., Lohmann, D., et al. (2011). Anthropogenic Greenhouse Gas Contribution to Flood Risk in England and Wales in Autumn 2000. Nature, 470(7334), 382-385. doi:10.1038/nature09762

Pall, P., Allen, M. R., & Stone, D. A. (2006). Testing the Clausius--Clapeyron Constraint on Changes in Extreme Precipitation Under CO2 Warming. Climate Dynamics, 28(4), 351-363. doi:10.1007/s00382-006-0180-2 Piani, C., Frame, D. J., Stainforth, D. A., & Allen, M. R. (2005). Constraints on Climate Change from a Multi-Thousand Member Ensemble of Simulations. Geophysical Research Letters, 32(23). doi:10.1029/2005GL024452

Piani, C., Sanderson, B., Giorgi, F., Frame, D. J., Christensen, C., & Allen, M. R. (2007). Regional Probabilistic Climate Forecasts from a Multithousand, Multimodel Ensemble of Simulations. Journal of Geophysical Research, 112. doi:10.1029/2007JD008712

Stainforth, D. A., Aina, T., Christensen, C., Collins, M., Faull, N. E., Frame, D. J., Kettleborough, J. A., et al. (2005). Uncertainty in Predictions of the Climate Response to Rising Levels of Greenhouse Gases. Nature, 433(7024), 403-406. doi:10.1038/nature03301

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DIMES

Allalouf, M., Kaplan, E., & Shavitt, Y. (2009). On the Feasibility of a Large Scale Distributed Testbed for Measuring Quality of Path Characteristics in the Internet. 5th International Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities and Workshops, 2009 (pp. 1-6). Washington, DC, USA.

Almog, A., Goldberger, J., & Shavitt, Y. (2008). Unifying Unknown Nodes in the Internet Graph Using Semisupervised Spectral Clustering. International Conference on Data Mining Workshops, 2008 (pp. 174-183). doi:10.1109/ICDMW.2008.12

Buchanan, M. (2005). DISTRIBUTED COMPUTING: Data-Bots Chart the Internet. Science, 308(5723), 813. doi:10.1126/science.308.5723.813

Carmi, S., Havlin, S., Kirkpatrick, S., Shavitt, Y., & Shir, E. (2007). From the Cover: A Model of Internet Topology Using K-Shell Decomposition. Proceedings of the National Academy of Sciences, 104(27), 11150-11154. doi:10.1073/pnas.0701175104

Cronin, E., Jamin, S., Jin, C., Kurc, A. R., Raz, D., & Shavitt, Y. (2002). Constrained Mirror Placement on the Internet. IEEE Journal on Selected Areas in Communications, 20(7), 1369-1382. doi:10.1109/JSAC.2002.802066

Dolev, D., Mokryn, O., & Shavitt, Y. (2003). On Multicast Trees: Structure and Size Estimation. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications (Vol. 2, pp. 1011-1021). doi:10.1109/INFCOM.2003.1208938

Feldman, D., & Shavitt, Y. (2008). Automatic Large Scale Generation of Internet PoP Level Maps. Global Telecommunications Conference, 2008 (pp. 1-6). doi:10.1109/GLOCOM.2008.ECP.466

Francis, P., Jamin, S., Jin, C., Jin, Y., Raz, D., Shavitt, Y., & Zhang, L. (2001). IDMaps: A Global Internet Host Distance Estimation Service. IEEE Transactions on Networking, 9(5), 525-540. doi:10.1109/90.958323

Gonen, M., & Shavitt, Y. (2009). Approximating the Number of Network Motifs. Internet Mathematics, 6(3), 349-372. doi:10.1080/15427951.2009.10390645

Raz, D., Shavitt, Y., & Zhang, L. (2004). Distributed Council Election. IEEE Transactions on Networking, 12(3), 483-492. doi:10.1109/TNET.2004.828945

Shavitt, Y., & Shir, E. (2005). DIMES: Let the Internet Measure Itself. ACM SIGCOMM Computer Communication Review, 35(5), 71-74. doi:10.1145/1096536.1096546

Shavitt, Y., & Singer, Y. (2007). Beyond Centrality---classifying Topological Significance Using Backup Efficiency and Alternative Paths. New Journal of Physics, 9, 266-283. doi:10.1088/1367-2630/9/8/266

Shavitt, Y., & Singer, Y. (2008). Trading Potatoes in Distributed Multi-Tier Routing Systems. Proceedings of the 3rd International Workshop on Economics of Networked Systems (pp. 67-72). Seattle, WA, USA. doi:10.1145/1403027.1403042

Shavitt, Y., & Tankel, T. (2004). On the Curvature of the Internet and Its Usage for Overlay Construction and Distance Estimation. Twenty-Third AnnualJoint Conference of the IEEE Computer and Communications Societies (Vol. 1). doi:10.1109/INFCOM.2004.1354510

Shavitt, Y., & Tankel, T. (2004). Big-Bang Simulation for Embedding Network Distances in Euclidean Space. IEEE Transactions on Networking, 12(6), 993-1006. doi:10.1109/TNET.2004.838597

Shavitt, Y., & Tankel, T. (2008). Hyperbolic Embedding of Internet Graph for Distance Estimation and Overlay Construction. IEEE Transactions on Networking, 16(1), 25-36. doi:10.1109/TNET.2007.899021

Shavitt, Y., & Weinsberg, U. (2009). Quantifying the Importance of Vantage Points Distribution in Internet Topology Measurements. IEEE INFOCOM 2009 (pp. 792-800). Rio de Janeiro, Brazil. doi:10.1109/INFCOM.2009.5061988

Shavitt, Y., Sun, X., Wool, A., & Yener, B. (2004). Computing the Unmeasured: An Algebraic Approach to Internet Mapping. IEEE Journal on Selected Areas in Communications, 22(1), 67-78. doi:10.1109/JSAC.2003.818796

Weinsberg, U., Shavitt, Y., & Shir, E. (2007). Near-Deterministic Inference of AS Relationships. INFOCOM Workshops 2009 (pp. 1-2). Rio de Janeiro, Brazil. doi:10.1109/INFCOMW.2009.5072167

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Einstein@home

Übersicht auf der Einstein@home Projektwebseite: https://einsteinathome.org/de/science/publications.

Abbott, B. P., Abbott, R., Adhikari, R., Ajith, P., Allen, B., Allen, G., Amin, R. S., et al. (2009). Einstein@Home Search for Periodic Gravitational Waves in LIGO S4 Data. Physical Review D, 79(2), 2001-2030. doi:10.1103/PhysRevD.79.022001

Abbott, B. P., Abbott, R., Adhikari, R., Ajith, P., Allen, B., Allen, G., Amin, R. S., et al. (2009). Einstein@Home Search for Periodic Gravitational Waves in Early S5 LIGO Data. Physical Review D, 80(4), 2003-2027. doi:10.1103/PhysRevD.80.042003

Allen, B. (2007). Einstein@Home S3 Analysis Summary. Retrieved from http://einstein.phys.uwm.edu/FinalS3Results/

Knispel, B., Allen, B., Cordes, J. M., Deneva, J. S., Anderson, D. P., Aulbert, C., Bhat, N. D. R., et al. (2010). Pulsar Discovery by Global Volunteer Computing. Science, 329(5997), 1305. doi:10.1126/science.1195253

Knispel, B., Lazarus, P., Allen, B., Anderson, D. P., Aulbert, C., Bhat, N. D. R., Bock, O., et al. (2011). ARECIBO PALFA Survey And Einstein@Home: Binary Pulsar Discovery By Volunteer Computing. The Astrophysical Journal, 732(1), L1. doi:10.1088/2041-8205/732/1/L1

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EOn

Henkelman, G., & Jónsson, H. (2003). Multiple Time Scale Simulations of Metal Crystal Growth Reveal the Importance of Multiatom Surface Processes. Physical Review Letters, 90(11). doi:10.1103/PhysRevLett.90.116101

Xu, L., & Henkelman, G. (2008). Adaptive Kinetic Monte Carlo for First-Principles Accelerated Dynamics. The Journal of Chemical Physics, 129(11), 114104. doi:10.1063/1.2976010

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EulerNet (teilweise in Yoyo@home gelaufen)

Gerbicz, R., Meyrignac, J.-C., & Beckert, U. (2011). All solutions of the Diophantine equation a^6+b^6=c^6+d^6+e^6+f^6+g^6 for a,b,c,d,e,f,g < 250000 found with a distributed Boinc project. arXiv:1108.0462

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Evolution@home (teilweise in Yoyo@home gelaufen)

Loewe, L. (2002). Global Computing for Bioinformatics. Briefings in Bioinformatics, 3(4), 377-388. doi:10.1093/bib/3.4.377

Loewe, L. (2005) Evolution@home: Global computing quantifies evolution due to Muller's ratchet. BMC Bioinformatics. DOI: 10.1186/1471-2105-6-S3-P18.

Loewe, L. (2006). Quantifying the Genomic Decay Paradox Due to Muller's Ratchet in Human Mitochondrial DNA. Genetical Research, 87(2), 133-159. doi:10.1017/S0016672306008123

Loewe, L. (2007). Evolution@home: observations on participant choice, work unit variation and low-effort global computing. Software: Practice and Experience. DOI: 10.1002/spe.806.

Loewe, L. & Lamatsch, D.K. (2008) Quantifying the threat of extinction from Muller's ratchet in the diploid Amazon molly (Poecilia formosa). BMC Evolutionary Biology. DOI: 10.1186/1471-2148-8-88.

Loewe, L., & Cutter, A. D. (2008). On the Potential for Extinction by Muller's Ratchet in Caenorhabditis Elegans. BMC Evolutionary Biology, 8, 125. doi:10.1186/1471-2148-8-125

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Waxman, D. & Loewe, L. A stochastic model for a single click of Muller's ratchet. Journal of Theoretical Biology. DOI: 10.1016/j.jtbi.2010.03.014.

Folding@home

Bacallado, S., Chodera, J. D., & Pande, V. S. (2009). Bayesian Comparison of Markov Models of Molecular Dynamics with Detailed Balance Constraint. Journal of Chemical Physics, 131(4), 5106-5116. doi:10.1063/1.3192309

Beauchamp, K. A., Ensign, D. L., Das, R., & Pande, V. S. (2011). Quantitative Comparison of Villin Headpiece Subdomain Simulations and Triplet--triplet Energy Transfer Experiments. Proceedings of the National Academy of Sciences, 108(31), 12734-12739. doi:10.1073/pnas.1010880108

Beberg, A. L., & Pande, V. S. (2007). Storage@home: Petascale Distributed Storage. Parallel and Distributed Processing Symposium, 2007 (pp. 1-6). Long Beach, CA , USA. doi:10.1109/IPDPS.2007.370672

Beberg, A. L., Ensign, D. L., Jayachandran, G., Khaliq, S., & Pande, V. S. (2009). Folding@Home: Lessons from Eight Years of Volunteer Distributed Computing. IEEE International Symposium on Prallel & Distributed Processing 2009, 1-8. IEEE. doi:10.1109/IPDPS.2009.5160922

Bowman, G. R., & Pande, V. S. (2009). The Roles of Entropy and Kinetics in Structure Prediction. PLoS One, 4(6), e5840. doi:10.1371/journal.pone.0005840

Bowman, G. R., & Pande, V. S. (2010). Protein Folded States Are Kinetic Hubs. Proceedings of the National Academy of Sciences, 107(24), 10890-10895. doi:10.1073/pnas.1003962107

Bowman, G. R., Ensign, D. L., & Pande, V. S. (2010). Enhanced Modeling Via Network Theory: Adaptive Sampling of Markov State Models. Journal of Chemical Theory and Computation, 6(3), 787-794. doi:10.1021/ct900620b

Bowman, G. R., Huang, X., & Pande, V. S. (2009). Using Generalized Ensemble Simulations and Markov State Models to Identify Conformational States. Methods, 49(2), 197-201. doi:10.1016/j.ymeth.2009.04.013

Bowman, G. R., Huang, X., & Pande, V. S. (2010). Network Models for Molecular Kinetics and Their Initial Applications to Human Health. Cell Research, 20(6), 622-630. doi:10.1038/cr.2010.57

Bowman, G. R., Huang, X., Yao, Y., Sun, J., Carlsson, G., Guibas, L. J., & Pande, V. S. (2008). Structural Insight into RNA Hairpin Folding Intermediates. Journal of the American Chemical Society, 130(30), 9676-9678. doi:10.1021/ja8032857

Bowman, G. R., Voelz, V. A., & Pande, V. S. (2010). Atomistic Folding Simulations of the Five-Helix Bundle Protein λ₆₋₈₅. Journal of the American Chemical Society, 133(4), 664-667. doi:10.1021/ja106936n

Bowman, G. R., Voelz, V. A., & Pande, V. S. (2011). Taming the Complexity of Protein Folding. Current Opinion in Structural Biology, 21(1), 4-11. doi:10.1016/j.sbi.2010.10.006

Chodera, J. D., Singhal, N., Pande, V. S., Dill, K. A., & Swope, W. C. (2007). Automatic Discovery of Metastable States for the Construction of Markov Models of Macromolecular Conformational Dynamics. Journal of Chemical Physics, 126(15), 5101-5118. doi:10.1063/1.2714538

Chong, L. T., Snow, C. D., Rhee, Y. M., & Pande, V. S. (2005). Dimerization of the P53 Oligomerization Domain: Identification of a Folding Nucleus by Molecular Dynamics Simulations. Journal of Molecular Biology, 345(4), 869-878. doi:10.1016/j.jmb.2004.10.083

Chong, L. T., Swope, W. C., Pitera, J. W., & Pande, V. S. (2006). Kinetic Computational Alanine Scanning: Application to P53 Oligomerization. Journal of Molecular Biology, 357(3), 1039-1049. doi:10.1016/j.jmb.2005.12.083

DeGrado, B., & Dalby, P. (1999). Engineering and Design. Current Opinion in Structural Biology, 9(4), 450-451. doi:10.1016/j.sbi.2011.06.003

DePaul, A. J., Thompson, E. J., Patel, S. S., Haldeman, K., & Sorin, E. J. (2010). Equilibrium Conformational Dynamics in an RNA Tetraloop from Massively Parallel Molecular Dynamics. Nucleic Acids Research, 38(14), 4856-4867. doi:10.1093/nar/gkq134

Eastman, P., & Pande, V. S. (2010). OpenMM: A Hardware Abstraction Layer for Molecular Simulations. Computing in Science and Engineering, 12(4), 34-39. doi:10.1109/MCSE.2010.27

Elmer, S. P., Park, S., & Pande, V. S. (2005). Foldamer Dynamics Expressed Via Markov State Models. I. Explicit Solvent Molecular-Dynamics Simulations in Acetonitrile, Chloroform, Methanol, and Water. Journal of Chemical Physics, 123(11), 4902-4916. doi:10.1063/1.2001648

Elmer, S. P., Park, S., & Pande, V. S. (2005). Foldamer Dynamics Expressed Via Markov State Models. II. State Space Decomposition. Journal of Chemical Physics, 123(11), 4903-4910. doi:10.1063/1.2008230

Elsen, E., Vishal, V., Houston, M., Pande, V. S., Hanrahan, P., & Darve, E. (2007). N-Body Simulation on GPUs. Computational Engineering, Finance, and Science. Tampa, Florida, USA: ACM. doi:10.1145/1188455.1188649 arXiv:0706.3060

Ensign, D. L., & Pande, V. S. (2009). The Fip35 WW Domain Folds with Structural and Mechanistic Heterogeneity in Molecular Dynamics Simulations. Biophysical Journal, 96(8), L53-L55. doi:10.1016/j.bpj.2009.01.024

Ensign, D. L., Kasson, P. M., & Pande, V. S. (2007). Heterogeneity Even at the Speed Limit of Folding: Large-Scale Molecular Dynamics Study of a Fast-Folding Variant of the Villin Headpiece. Journal of Molecular Biology, 374(3), 806-816. doi:10.1016/j.jmb.2007.09.069

Friedrichs, M. S., Eastman, P., Vaidyanathan, V., Houston, M., Legrand, S., Beberg, A. L., Ensign, D. L., et al. (2009). Accelerating Molecular Dynamic Simulation on Graphics Processing Units. Journal of Computational Chemistry, 30(6), 864-872. doi:10.1002/jcc.21209

Fujitani, H., Tanida, Y., Ito, M., Jayachandran, G., Snow, C. D., Shirts, M. R., Sorin, E. J., et al. (2005). Direct Calculation of the Binding Free Energies of FKBP Ligands. Journal of Chemical Physics, 123(8), 4108-4113. doi:10.1063/1.1999637

Haque, I. S., & Pande, V. S. (2010). Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in Gpgpu. Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (pp. 691-696). IEEE Computer Society. doi:10.1109/CCGRID.2010.84

Haque, I. S., & Pande, V. S. (2011). 'Large-Scale Chemical Informatics on the GPU. In W.-M. W. Hwu (Ed.), GPU Computing Gems (Emerald Ed.). Morgan Kaufmann.

Hinrichs, N. S., & Pande, V. S. (2007). Calculation of the Distribution of Eigenvalues and Eigenvectors in Markovian State Models for Molecular Dynamics. Journal of Chemical Physics, 126(24), 4101-4112. doi:10.1063/1.2740261

Huang, X., Bowman, G. R., & Pande, V. S. (2008). Convergence of Folding Free Energy Landscapes Via Application of Enhanced Sampling Methods in a Distributed Computing Environment. Journal of Chemical Physics, 128(20), 5106-5121. doi:10.1063/1.2908251

Jayachandran, G., Shirts, M. R., Park, S., & Pande, V. S. (2006). Parallelized-over-Parts Computation of Absolute Binding Free Energy with Docking and Molecular Dynamics. Journal of Chemical Physics, 125(8), 4901-4913. doi:10.1063/1.2221680

Jayachandran, G., Vishal, V., & Pande, V. S. (2006). Using Massively Parallel Simulation and Markovian Models to Study Protein Folding: Examining the Dynamics of the Villin Headpiece. Journal of Chemical Physics, 124(16), 4902-4914. doi:10.1063/1.2186317

Jayachandran, G., Vishal, V., García, A. E., & Pande, V. S. (2007). Local Structure Formation in Simulations of Two Small Proteins. Journal of Structural Biology, 157(3), 491-499. doi:10.1016/j.jsb.2006.10.001

Kasson, P. M., & Pande, V. S. (2006). Predicting Structure and Dynamics of Loosely-Ordered Protein Complexes: Influenza Hemagglutinin Fusion Peptide. In R. B. Altman, A. K. Dunker, L. Hunter, T. Murray, & T. E. Klein (Eds.), Pacific Symposium on Biocomputing 2007 (pp. 40-50). Maui, Hawaii, USA: World Scientific Publishing Co. doi:10.1142/9789812772435_0005

Kasson, P. M., & Pande, V. S. (2007). Control of Membrane Fusion Mechanism by Lipid Composition: Predictions from Ensemble Molecular Dynamics. PLoS Computational Biology, 3(11), e220. doi:10.1371/journal.pcbi.0030220

Kasson, P. M., & Pande, V. S. (2009). Combining Mutual Information with Structural Analysis to Screen for Functionally Important Residues in Influenza Hemagglutinin. In R. B. Altman, A. K. Dunker, L. Hunter, T. Murray, & T. E. Klein (Eds.), Pacific Symposium on Biocomputing 2009 (pp. 492-503). Kohala Coast, Hawaii, USA: World Scientific Publishing Co. doi:10.1142/9789812836939_0047

Kasson, P. M., Ensign, D. L., & Pande, V. S. (2009). Combining Molecular Dynamics with Bayesian Analysis to Predict and Evaluate Ligand-Binding Mutations in Influenza Hemagglutinin. Journal of the American Chemical Society, 131(32), 11338-11340. doi:10.1021/ja904557w

Kasson, P. M., Kelley, N. W., Singhal, N., Vrljic, M., Brunger, A. T., & Pande, V. S. (2006). Ensemble Molecular Dynamics Yields Submillisecond Kinetics and Intermediates of Membrane Fusion. Proceedings of the National Academy of Sciences, 103(32), 11916-11921. doi:10.1073/pnas.0601597103

Kasson, P. M., Lindahl, E., & Pande, V. S. (2010). Atomic-Resolution Simulations Predict a Transition State for Vesicle Fusion Defined by Contact of a Few Lipid Tails. PLoS Computational Biology, 6(6), e1000829. doi:10.1371/journal.pcbi.1000829

Kasson, P. M., Lindahl, E., & Pande, V. S. (2011). Water Ordering at Membrane Interfaces Controls Fusion Dynamics. Journal of the American Chemical Society, 133(11), 3812-3815. doi:10.1021/ja200310d

Kasson, P. M., Zomorodian, A., Park, S., Singhal, N., Guibas, L. J., & Pande, V. S. (2007). Persistent Voids: a New Structural Metric for Membrane Fusion. Bioinformatics, 23(14), 1753-1759. doi:10.1093/bioinformatics/btm250

Kelley, N. W., Huang, X., Tam, S., Spiess, C., Frydman, J., & Pande, V. S. (2009). The Predicted Structure of the Headpiece of the Huntingtin Protein and Its Implications on Huntingtin Aggregation. Journal of Molecular Biology, 388(5), 919-927. doi:10.1016/j.jmb.2009.01.032

Kelley, N. W., Vishal, V., Krafft, G. A., & Pande, V. S. (2008). Simulating Oligomerization at Experimental Concentrations and Long Timescales: A Markov State Model Approach. Journal of Chemical Physics, 129(21), 4707-4717. doi:10.1063/1.3010881

Larson, S. M., Snow, C. D., Shirts, M. R., & Pande, V. S. (2004). Folding@home and Genome@Home: Using Distributed Computing to Tackle Previously Intractable Problems in Computational Biology. In R. P. Grant (Ed.), Computational Genomics. Horizon Bioscience. Retrieved from http://fah-web.stanford.edu/papers/Horizon_Review.pdf

Lucent, D., Snow, C. D., Aitken, C. E., & Pande, V. S. (2010). Non-Bulk-Like Solvent Behavior in the Ribosome Exit Tunnel. PLoS Computational Biology, 6(10), e1000963. doi:10.1371/journal.pcbi.1000963

Lucent, D., Vishal, V., & Pande, V. S. (2007). Protein Folding Under Confinement: a Role for Solvent. Proceedings of the National Academy of Sciences, 104(25), 10430-10434. doi:10.1073/pnas.0608256104

Luttmann, E., Ensign, D. L., Vaidyanathan, V., Houston, M., Rimon, N., Øland, J., Jayachandran, G., et al. (2009). Accelerating Molecular Dynamic Simulation on the Cell Processor and Playstation 3. Journal of Computational Chemistry, 30(2), 268-274. doi:10.1002/jcc.21054

Pande, V. S. (2010). Simple Theory of Protein Folding Kinetics. Physical Review Letters, 105(19), 8101-8105. doi:10.1103/PhysRevLett.105.198101

Pande, V. S., Baker, I., Chapman, J., Elmer, S. P., Khaliq, S., Larson, S. M., Rhee, Y. M., et al. (2002). Atomistic Protein Folding Simulations on the Submillisecond Timescale Using Worldwide Distributed Computing. Biopolymers, 68. doi:10.1002/bip.10219

Pande, V. S., Beauchamp, K. A., & Bowman, G. R. (2010). Everything You Wanted to Know About Markov State Models but Were Afraid to Ask. Methods, 52(1), 99-105. doi:10.1016/j.ymeth.2010.06.002

Park, S., & Pande, V. S. (2006). Validation of Markov State Models Using Shannon's Entropy. Journal of Chemical Physics, 124(5), 4118-4123. doi:10.1063/1.2166393

Park, S., Ensign, D. L., & Pande, V. S. (2006). Bayesian Update Method for Adaptive Weighted Sampling. Physical Review E, 74(6), 6703-6715. doi:10.1103/PhysRevE.74.066703

Park, S., Radmer, R. J., Klein, T. E., & Pande, V. S. (2005). A New Set of Molecular Mechanics Parameters for Hydroxyproline and Its Use in Molecular Dynamics Simulations of Collagen-Like Peptides. Journal of Computational Chemistry, 26(15), 1612-1616. doi:10.1002/jcc.20301

Petrone, P. M., & Pande, V. S. (2006). Can Conformational Change Be Described by Only a Few Normal Modes? Biophysical Journal, 90(5), 1583-1593. doi:10.1529/biophysj.105.070045

Petrone, P. M., Snow, C. D., Lucent, D., & Pande, V. S. (2008). Side-Chain Recognition and Gating in the Ribosome Exit Tunnel. Proceedings of the National Academy of Sciences, 105(43), 16549-16554. doi:10.1073/pnas.0801795105

Ponder, J. W., Wu, C., Ren, P., Pande, V. S., Chodera, J. D., Schnieders, M. J., Haque, I. S., et al. (2010). Current Status of the AMOEBA Polarizable Force Field. The Journal of Physical Chemistry B, 114(8), 2549-2564. doi:10.1021/jp910674d

Rajadas, J., Liu, C. W., Novick, P., Kelley, N. W., Inayathullah, M., LeMieux, M. C., & Pande, V. S. (2011). Rationally Designed Turn Promoting Mutation in the Amyloid-? Peptide Sequence Stabilizes Oligomers in Solution. PLoS One, 6(7), e21776. doi:10.1371/journal.pone.0021776

Rhee, Y. M., & Pande, V. S. (2003). Multiplexed-Replica Exchange Molecular Dynamics Method for Protein Folding Simulation. Biophysical Journal, 84(2), 775-786. doi:10.1016/S0006-3495(03)74897-8

Rhee, Y. M., & Pande, V. S. (2006). On the Role of Chemical Detail in Simulating Protein Folding Kinetics. Chemical Physics, 323(1), 66-77. doi:10.1016/j.chemphys.2005.08.060

Rhee, Y. M., Sorin, E. J., Jayachandran, G., Lindahl, E., & Pande, V. S. (2004). Simulations of the Role of Water in the Protein-Folding Mechanism. Proceedings of the National Academy of Sciences, 101(17), 6456-6461. doi:10.1073/pnas.0307898101

Shirts, M. R., & Pande, V. S. (2000). Screen Savers of the World Unite! Science, 290(5498), 1903-1904. doi:10.1126/science.290.5498.1903

Shirts, M. R., & Pande, V. S. (2001). Mathematical Foundations of Ensemble Dynamics. Physical Review Letters, 86(22). doi:10.1103/PhysRevLett.86.4983

Shirts, M. R., & Pande, V. S. (2005). Solvation Free Energies of Amino Acid Side Chain Analogs for Common Molecular Mechanics Water Models. Journal of Chemical Physics, 122(13), 4508-4521. doi:10.1063/1.1877132

Shirts, M. R., & Pande, V. S. (2005). Comparison of Efficiency and Bias of Free Energies Computed by Exponential Averaging, the Bennett Acceptance Ratio, and Thermodynamic Integration. Journal of Chemical Physics, 122(14), 4107-4123. doi:10.1063/1.1873592

Shirts, M. R., Bair, E., Hooker, G., & Pande, V. S. (2003). Equilibrium Free Energies from Nonequilibrium Measurements Using Maximum-Likelihood Methods. Physical Review Letters, 91(14), 114605-140601. doi:10.1103/PhysRevLett.91.140601

Shirts, M. R., Pitera, J. W., Swope, W. C., & Pande, V. S. (2003). Extremely Precise Free Energy Calculations of Amino Acid Side Chain Analogs: Comparison of Common Molecular Mechanics Force Fields for Proteins. Journal of Chemical Physics, 119(11), 5740-5762. doi:10.1063/1.1587119

Singhal, N., & Pande, V. S. (2005). Error Analysis and Efficient Sampling in Markovian State Models for Molecular Dynamics. Journal of Chemical Physics, 123(20), 4909-4922. doi:10.1063/1.2116947

Singhal, N., Snow, C. D., & Pande, V. S. (2004). Using Path Sampling to Build Better Markovian State Models: Predicting the Folding Rate and Mechanism of a Tryptophan Zipper Beta Hairpin. Journal of Chemical Physics, 121(1), 415-426. doi:10.1063/1.1738647

Snow, C. D., Nguyen, H., Pande, V. S., & Gruebele, M. (2002). Absolute Comparison of Simulated and Experimental Protein-Folding Dynamics. Nature, 420(6911), 102-106. doi:10.1038/nature01160

Snow, C. D., Qiu, L., Du, D., Gai, F., Hagen, S. J., & Pande, V. S. (2004). Trp Zipper Folding Kinetics by Molecular Dynamics and Temperature-Jump Spectroscopy. Proceedings of the National Academy of Sciences, 101(12), 4077-4082. doi:10.1073/pnas.0305260101

Snow, C. D., Rhee, Y. M., & Pande, V. S. (2006). Kinetic Definition of Protein Folding Transition State Ensembles and Reaction Coordinates. Biophysical Journal, 91(1), 14-24. doi:10.1529/biophysj.105.075689

Snow, C. D., Sorin, E. J., Rhee, Y. M., & Pande, V. S. (2005). How Well Can Simulation Predict Protein Folding Kinetics and Thermodynamics? Annual Reviews Biophysics and Biomolecular Structure, 34, 43-69. Annual Reviews. doi:10.1146/annurev.biophys.34.040204.144447

Snow, C. D., Zagrovic, B., & Pande, V. S. (2002). The Trp Cage: Folding Kinetics and Unfolded State Topology Via Molecular Dynamics Simulations. Journal of the American Chemical Society, 124(49), 14548-14549. doi:10.1021/ja028604l

Sorin, E. J., & Pande, V. S. (2005). Empirical Force-Field Assessment: The Interplay Between Backbone Torsions and Noncovalent Term Scaling. Journal of Computational Chemistry, 26(7), 682-690. doi:10.1002/jcc.20208

Sorin, E. J., & Pande, V. S. (2005). Exploring the Helix-Coil Transition Via All-Atom Equilibrium Ensemble Simulations. Biophysical Journal, 88(4), 2472-2493. doi:10.1529/biophysj.104.051938

Sorin, E. J., & Pande, V. S. (2006). Nanotube Confinement Denatures Protein Helices. Journal Of The American Chemical Society, 128(19), 6316-6317. doi:10.1021/ja060917j

Sorin, E. J., Nakatani, B. J., Rhee, Y. M., Jayachandran, G., Vishal, V., & Pande, V. S. (2004). Does Native State Topology Determine the RNA Folding Mechanism? Journal of Molecular Biology, 337(4), 789-797. doi:10.1016/j.jmb.2004.02.024

Sorin, E. J., Rhee, Y. M., & Pande, V. S. (2005). Does Water Play a Structural Role in the Folding of Small Nucleic Acids? Biophysical Journal, 88(4), 2516-2524. doi:10.1529/biophysj.104.055087

Sorin, E. J., Rhee, Y. M., Nakatani, B. J., & Pande, V. S. (2003). Insights into Nucleic Acid Conformational Dynamics from Massively Parallel Stochastic Simulations. Biophysical Journal, 85(2), 790-803. doi:10.1016/S0006-3495(03)74520-2

Sorin, E. J., Rhee, Y. M., Shirts, M. R., & Pande, V. S. (2006). The Solvation Interface Is a Determining Factor in Peptide Conformational Preferences. Journal of Molecular Biology, 356(1), 248-256. doi:10.1016/j.jmb.2005.11.058

Suydam, I. T., Snow, C. D., Pande, V. S., & Boxer, S. G. (2006). Electric Fields at the Active Site of an Enzyme: Direct Comparison of Experiment with Theory. Science, 313(5784), 200-204. doi:10.1126/science.1127159

Thompson, E. J., DePaul, A. J., Patel, S. S., & Sorin, E. J. (2010). Evaluating Molecular Mechanical Potentials for Helical Peptides and Proteins. PLoS One, 5(4), e10056. doi:10.1371/journal.pone.0010056

Voelz, V. A., Bowman, G. R., Beauchamp, K. A., & Pande, V. S. (2010). Molecular Simulation of Ab Initio Protein Folding for a Millisecond Folder NTL9 (1- 39). Journal of the American Chemical Society, 132(5), 1526-1528. doi:10.1021/ja9090353

Voelz, V. A., Luttmann, E., Bowman, G. R., & Pande, V. S. (2009). Probing the Nanosecond Dynamics of a Designed Three-Stranded Beta-Sheet with a Massively Parallel Molecular Dynamics Simulation. International Journal of Molecular Sciences, 10(3), 1013-1030. doi:10.3390/ijms10031013

Voelz, V. A., Petrone, P. M., & Pande, V. S. (2009). A Multiscale Approach to Sampling Nascent Peptide Chains in the Ribosomal Exit Tunnel. Pacific Symposium on Biocomputing 2009 (pp. 340-352). Kohala Coast, Hawaii, USA: World Scientific Pub Co Inc. Retrieved from http://psb.stanford.edu/psb-online/proceedings/psb09/voelz.pdf

Voelz, V. A., Singh, V. R., Wedemeyer, W. J., Lapidus, L. J., & Pande, V. S. (2010). Unfolded-State Dynamics and Structure of Protein L Characterized by Simulation and Experiment. Journal of the American Chemical Society, 132(13), 4702-4709. doi:10.1021/ja908369h

Wagoner, J. A., & Pande, V. S. (2011). A Smoothly Decoupled Particle Interface: New Methods for Coupling Explicit and Implicit Solvent. Journal of Chemical Physics, 134(21), 4103-4116. doi:10.1063/1.3595262

Zagrovic, B., & Pande, V. S. (2003). Structural Correspondence Between the Alpha-Helix and the Random-Flight Chain Resolves How Unfolded Proteins Can Have Native-Like Properties. Nature Structural Biology, 10(11), 955-961. doi:10.1038/nsb995

Zagrovic, B., & Pande, V. S. (2003). Solvent Viscosity Dependence of the Folding Rate of a Small Protein: Distributed Computing Study. Journal of Computational Chemistry, 24(12), 1432-1436. doi:10.1002/jcc.10297

Zagrovic, B., Jayachandran, G., Millett, I. S., Doniach, S., & Pande, V. S. (2005). How Large Is an Î?-Helix? Studies of the Radii of Gyration of Helical Peptides by Small-Angle X-Ray Scattering and Molecular Dynamics. Journal of Molecular Biology, 353(2), 232-241. doi:10.1016/j.jmb.2005.08.053

Zagrovic, B., Lipfert, J., Sorin, E. J., Millett, I. S., Van Gunsteren, W. F., Doniach, S., & Pande, V. S. (2005). Unusual Compactness of a Polyproline Type II Structure. Proceedings of the National Academy of Sciences, 102(33), 11698-11703. doi:10.1073/pnas.0409693102

Zagrovic, B., Snow, C. D., Khaliq, S., Shirts, M. R., & Pande, V. S. (2002). Native-Like Mean Structure in the Unfolded Ensemble of Small Proteins. Journal of Molecular Biology, 323(1), 153-164. doi:10.1016/S0022-2836(02)00888-4

Zagrovic, B., Snow, C. D., Shirts, M. R., & Pande, V. S. (2002). Simulation of Folding of a Small Alpha-Helical Protein in Atomistic Detail Using Worldwide-Distributed Computing. Journal of Molecular Biology, 323(5), 927-937. doi:10.1016/S0022-2836(02)00997-X

Zagrovic, B., Sorin, E. J., & Pande, V. S. (2001). B-Hairpin Folding Simulations in Atomistic Detail Using an Implicit Solvent Model. Journal of Molecular Biology, 313(1). doi:10.1006/jmbi.2001.5033

Folding@home relevante Artikel, die nicht vom Folding@home Team stammen:

Paci E, Cavalli A, Vendruscolo M, Caflisch A. (2003). Analysis of the distributed computing approach applied to the folding of a small beta peptide. Proc Natl Acad Sci U S A. 2003 Jul 8;100(14):8217-22. Epub 2003 Jun 18.

Marianayagam NJ, Fawzi NL, Head-Gordon T. (2003). Protein folding by distributed computing and the denatured state ensemble. Proc Natl Acad Sci U S A. 2005 Nov 15;102(46):16684-9. Epub 2005 Nov 2.

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Genome@home

Larson, S. M., & Pande, V. S. (2003). Sequence Optimization for Native State Stability Determines the Evolution and Folding Kinetics of a Small Protein. Journal of Molecular Biology, 332(1), 275-286. doi:10.1016/S0022-2836(03)00832-5

Larson, S. M., England, J. L., Desjarlais, J. R., & Pande, V. S. (2002). Thoroughly Sampling Sequence Space: Large-Scale Protein Design of Structural Ensembles. Protein Science, 11(12), 2804-2813. doi:10.1110/ps.0203902

Larson, S. M., Garg, A., Desjarlais, J. R., & Pande, V. S. (2003). Increased Detection of Structural Templates Using Alignments of Designed Sequences. Proteins, 51(3), 390-396. doi:10.1002/prot.10346

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Harmonious Trees (komplett als Teil von Yoyo@home gelaufen)

Fang, Wenjie & Beckert, U. (2018) Parallel Tree Search in Volunteer Computing: a Case Study. Journal of Grid Computing. DOI: 10.1007/s10723-017-9411-5.

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HashClash

Stevens, M. M. J. (2006). Fast Collision Attack on MD5. Retrieved from http://www.win.tue.nl/hashclash/fastcoll.pdf

Stevens, M. M. J., Lenstra, A., & De Weger, B. M. M. (2997). Chosen-Pre?x Collisions for MD5 and Colliding X.509 Certificates for Different Identities. In M. Naor (Ed.), Springer Lecture Notes in Computer Science (Vol. 4515, pp. 1-22). Barcelona, Spain: Springer. Retrieved from http://www.win.tue.nl/hashclash/EC07v2.0.pdf

Stevens, M. M. J., De Weger, B. M. M., Schmitz, G., & Van Tilborg, H. C. A. (2007). On Collisions for MD5, TU Eindhoven MSc Thesis, June 2007. Eindhoven University of Technology, Eindhoven, Netherlands. Retrieved from http://www.win.tue.nl/hashclash/On Collisions for MD5 - M.M.J. Stevens.pdf

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Ibercivis

Simões, C. J. V., Rivero, A., & Brito, R. M. M. (2010). Searching for Anti-Amyloid Drugs with the Help of Citizens: the "AMILOIDE" Project on the IBERCIVIS Platform. ERCIM News, 82, 25-26. Retrieved from http://ercim-news.ercim.eu/en82/special/searching-for-anti-amyloid-drugs-with-the-help-of-citizens

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Lattice Project

Bazinet, A. L., & Cummings, M. P. (2007). The Lattice Project: a Grid Research and Production Environment Combining Multiple Grid Computing Models. In M. H. W. Weber (Ed.), Distributed & Grid Computing - Science Made Transparent for Everyone. Principles, Applications and Supporting Communities. In Press.

Bazinet, A. L., & Cummings, M. P. (2009). The Lattice Project: A Multi-Model Grid Computing System. University of Maryland. Retrieved from http://drum.lib.umd.edu/handle/1903/9892

Bazinet, A. L., & Cummings, M. P. (2011). Computing the Tree of Life - Leveraging the Power of Desktop and Service Grids. Fifth Workshop on Desktop Grids and Volunteer Computing Systems (PCGrid 2011). Anchorage, AK, USA. Retrieved from http://lattice.umiacs.umd.edu/latticefiles/publications/lattice/computing_tree_of_life.pdf

Bazinet, A. L., Myers, D. S., Fuetsch, J., & Cummings, M. P. (2007). Grid Services Base Library: A High-Level, Procedural Application Programming Interface for Writing Globus-Based Grid Services. Future Generation Computer Systems, 23(3), 517-522. doi:10.1016/j.future.2006.07.009

Cho, S., Zwick, A., Regier, J. C., Mitter, C., Cummings, M. P., Yao, J., Du, Z., et al. (2011). Can Deliberately Incomplete Gene Sample Augmentation Improve a Phylogeny Estimate for the Advanced Moths and Butterflies (Hexapoda: Lepidoptera)? Systematic Biology. doi:[http://dx.doi.org/10.1093/sysbio/syr079

Cummings, M. P., & Huskamp, J. C. (2005). Grid Computing. Educause Review, 40(6), 116-117.

Kawahara, A. Y., Ohshima, I., Kawakita, A., Regier, J. C., Mitter, C., Cummings, M. P., Davis, D. R., et al. (2011). Increased Gene Sampling Strengthens Support for Higher-Level Groups Within Leaf-Mining Moths and Relatives (Lepidoptera: Gracillariidae). BMC Evolutionary Biology, 11(1), 182. doi:10.1186/1471-2148-11-182

Lee, S., Wang, T. D., Hashmi, N., & Cummings, M. P. (2007). Bio-STEER: A Semantic Web Workflow Tool for Grid Computing in the Life Sciences. Future Generation Computer Systems, 23(3), 497-509. doi:10.1016/j.future.2006.07.011

Myers, D. S., & Bazinet, A. L. (2004). Intercepting Arbitrary Functions on Windows, UNIX, and Macintosh OS X Platforms. Center for Bioinformatics and Computational Biology, Institute for Advanced Computer Studies, University of Maryland, CS-TR-4585, UMIACS-TR-2004-28.

Myers, D. S., & Cummings, M. P. (2003). Necessity Is the Mother of Invention: a Simple Grid Computing System Using Commodity Tools. Journal of Parallel and Distributed Computing, 63(5), 578-589. doi:10.1016/S0743-7315(03)00004-2

Myers, D. S., Bazinet, A. L., & Cummings, M. P. (2007). Expanding the Reach of Grid Computing: Combining Globus-and BOINC-Based Systems. In E.-G. Talbi & A. Y. Zomaya (Eds.), Grid Computing for Bioinformatics and Computational Biology (p. 71). Hoboken, NJ, USA: John Wiley & Sons, Inc. doi:10.1002/9780470191637.ch4

Pettengill, J. B., & Neel, M. C. (2008). Phylogenetic Patterns and Conservation Among North American Members of the Genus Agalinis (Orobanchaceae). BMC Evolutionary Biology, 8, 264. doi:10.1186/1471-2148-8-264

Regier, J. C., & Zwick, A. (2011). Sources of Signal in 62 Protein-Coding Nuclear Genes for Higher-Level Phylogenetics of Arthropods. PLoS One, 6(8), e23408. doi:10.1371/journal.pone.0023408

Regier, J. C., Shultz, J. W., Zwick, A., Hussey, A., Ball, B., Wetzer, R., Martin, J. W., et al. (2010). Arthropod Relationships Revealed by Phylogenomic Analysis of Nuclear Protein-Coding Sequences. Nature, 463(7284), 1079-1083. doi:10.1038/nature08742

Regier, J. C., Zwick, A., Cummings, M. P., Kawahara, A. Y., Cho, S., Weller, S., Roe, A., et al. (2009). Toward Reconstructing the Evolution of Advanced Moths and Butterflies (Lepidoptera: Ditrysia): an Initial Molecular Study. BMC Evolutionary Biology, 9, 280. doi:10.1186/1471-2148-9-280

Reyna-Fabián, M. E., Laclette, J. P., Cummings, M. P., & García-Varela, M. (2010). Validating the Systematic Position of Plationus Segers, Murugan (Rotifera: Brachionidae) Using Sequences of the Large Subunit of the Nuclear Ribosomal DNA and of Cytochrome C Oxidase. Hydrobiologia, 644(1), 361-370. doi:10.1007/s10750-010-0203-1

Tishkoff, S. A., Gonder, M. K., Henn, B. M., Mortensen, H., Knight, A., Gignoux, C., Fernandopulle, N., et al. (2007). History of Click-Speaking Populations of Africa Inferred from MtDNA and Y Chromosome Genetic Variation. Molecular Biology and Evolution, 24(10), 2180-2195. doi:10.1093/molbev/msm155

Zwick, A., Regier, J. C., Mitter, C., & Cummings, M. P. (2010). Increased Gene Sampling Yields Robust Support for Higher-Level Clades Within Bombycoidea (Lepidoptera). Systematic Entomology, 36(1), 31-43. doi:10.1111/j.1365-3113.2010.00543.x

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LHC@home

McIntosh, E., Schmidt, F., & De Dinechin, F. (2006). Massive Tracking On Heterogeneous Platforms. Proceedings of ICAP 2006 (pp. 13-16). Chamonix, France.

Werner, H., Kaltchev, D. I., McIntosh, E., & Schmidt, F. (2006). Large Scale Beam-Beam Simulations for the CERN LHC Using Distributed Computing. 10th European Particle Accelerator Conference (p. 526). Edinburgh, UK. Retrieved from http://cdsweb.cern.ch/record/972345?ln=en

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Lifemapper

Stockwell DRB, Beach JH, Stewart A, Vorontsov G, Vieglais D, Scachetti Pereira R. (2006). The use of the GARP genetic algorithm and internet grid computing in the Lifemapper world atlas of species biodiversity. Online-Artikel.

Beach JH, Stewart AM, Vorontsov GY, Scachetti Pereira R, Stockwell DRB, Vieglais DA, Downie SR. The Future of Biodiversity: Mapping and Predicting the Distribution of Life with Distributed Computation. Online-Artikel.

Lifemapper relevante Artikel, die nicht vom Lifemapper Team stammen:

Shirley SM, Kark S. (2006). Amassing efforts against alien invasive species in Europe. PLoS Biol. 4(8):e279. doi:10.1371/journal.pbio.0040279.

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Malariacontrol

Bretscher, M. T., Maire, N., Chitnis, N., Felger, I., Owusu-Agyei, S., & Smith, T. A. (2011). The Distribution of Plasmodium Falciparum Infection Durations. Epidemics, 3(2), 109-118. doi:10.1016/j.epidem.2011.03.002

Carneiro, I., Smith, L. A., Ross, A., Roca-Feltrer, A., Greenwood, B., Schellenberg, J. A., Smith, T. A., et al. (2010). Intermittent Preventive Treatment for Malaria in Infants: a Decision-Support Tool for Sub-Saharan Africa. Bulletin of the World Health Organization, 88(11), 807-814. doi:10.2471/BLT.09.072397

Gosoniu, L., Vounatsou, P., Sogoba, N., Maire, N., & Smith, T. A. (2009). Mapping Malaria Risk in West Africa Using a Bayesian Nonparametric Non-Stationary Model. Computational Statistics & Data Analysis, 53(9), 3358-3371. doi:10.1016/j.csda.2009.02.022

Penny, M. A., Maire, N., Studer, A., Schapira, A., & Smith, T. A. (2008). What Should Vaccine Developers Ask? Simulation of the Effectiveness of Malaria Vaccines. PloS One, 3(9), e3193. doi:10.1371/journal.pone.0003193

Ross, A., & Smith, T. A. (2010). Interpreting Malaria Age-Prevalence and Incidence Curves: a Simulation Study of the Effects of Different Types of Heterogeneity. Malaria Journal, 9, 132. doi:10.1186/1475-2875-9-132

Ross, A., Maire, N., Sicuri, E., Smith, T. A., & Conteh, L. (2011). Determinants of the Cost-Effectiveness of Intermittent Preventive Treatment for Malaria in Infants and Children. PLoS One, 6(4), e18391. doi:10.1371/journal.pone.0018391

Ross, A., Penny, M. A., Maire, N., Studer, A., Carneiro, I., Schellenberg, D., Greenwood, B., et al. (2008). Modelling the Epidemiological Impact of Intermittent Preventive Treatment Against Malaria in Infants. PloS One, 3(7), e2661. doi:10.1371/journal.pone.0002661

Smith, T. A., Chitnis, N., Briët, O. J. T., & Tanner, M. (2011). Uses of Mosquito-Stage Transmission-Blocking Vaccines Against Plasmodium Falciparum. Trends in Parasitology, 27(5), 190-196. doi:10.1016/j.pt.2010.12.011

Smith, T. A., Maire, N., Ross, A., Penny, M. A., Chitnis, N., Schapira, A., Studer, A., et al. (2008). Towards a Comprehensive Simulation Model of Malaria Epidemiology and Control. Parasitology, 135(13), 1507-1516. doi:10.1017/S0031182008000371

Tediosi, F., Maire, N., Penny, M. A., Studer, A., & Smith, T. A. (2009). Simulation of the Cost-Effectiveness of Malaria Vaccines. Malaria Journal, 8(1), 127. doi:10.1186/1475-2875-8-127

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µFluids

Manning, R. E. (2006). Gas Bubble Stability In A Sphere Layer. Pardue University, West Lafayette, Indiana, USA. Retrieved from http://ufluids.net/files/Master_thesis.pdf

Manning, R. E., & Collicott, S. H. (2006). Bubble Penetration Through a Single Layer Sphere Bed. 45th AIAA Aerospace Sciences Meeting and Exhibit. DOI: 10.2514/6.2006-736

Braun, J. & Collicott, S. (2006). Zero-Gravity Stability of Droplets in a Bent Circular Cylinder. 44th AIAA Aerospace Sciences Meeting and Exhibit??. DOI: 10.2514/6.2006-732.

Braun, J. P. (2008). Zero Gravity Two-Phase Stability Solutions of Droplets in a Bent Circular Cylinder. Pardue University, West Lafayette, Indiana, USA. Retrieved from http://www.ufluids.net/ufluids/files/MSThesis_JPB_2008.pdf

Manning, R. & Collicott, S. (2010). Liquid Plugs in Rectangular Channels Under a Transverse Gravity Field'. 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. DOI: 10.2514/6.2010-1476.

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Milkyway@Home

Jake Weiss (2018). The stellar density of the major substructure in the Milky Way halo. milkyway.cs.rpi.edu/milkyway/media/jake_weiss_thesis.pdf (Dr. Arbeit)

Cole, N., Desell, T., Lombraña González, D., de Vega, F., Magdon-Ismail, M., Newberg, H. J., Szymanski, B. K., et al. (2010). Evolutionary Algorithms on Volunteer Computing Platforms: The MilkyWay@Home Project. In F. F. Vega & E. Cantú-Paz (Eds.), Parallel and Distributed Computational Intelligence (Vol. 269, pp. 63-90). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-10675-0_4

Cole, N., Newberg, H. J., Magdon-Ismail, M., Desell, T., Dawsey, K., Hayashi, W., Liu, X. F., et al. (2008). Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. The Astrophysical Journal, 683(2), 750-766. doi:10.1086/589681

Desell, T., Anderson, D. P., Magdon-Ismail, M., Newberg, H. J., Szymanski, B. K., & Varela, C. A. (2010). An Analysis of Massively Distributed Evolutionary Algorithms. IEEE Congress on Evolutionary Computation (pp. 1-8). Barcelona, Spain. doi:10.1109/CEC.2010.5586073

Desell, T., Cole, N., Magdon-Ismail, M., Newberg, H. J., Szymanski, B. K., & Varela, C. A. (2010). Distributed and Generic Maximum Likelihood Evaluation. Third IEEE International Conference on E-Science and Grid Computing (e-Science 2007) (pp. 337-344). Bangalore, India. doi:10.1109/E-SCIENCE.2007.30

Desell, T., Magdon-Ismail, M., Szymanski, B. K., Varela, C. A., Newberg, H. J., & Anderson, D. P. (2010). Validating Evolutionary Algorithms on Volunteer Computing Grids. In F. Eliassen & R. Kapitza (Eds.), Distributed Applications and Interoperable Systems (Vol. 6115, pp. 29-41). Berlin, Heidelberg: Springer Berlin Heidelberg. Retrieved from http://www.springerlink.com/index/10.1007/978-3-642-13645-0_3

Desell, T., Magdon-Ismail, M., Szymanski, B. K., Varela, C. A., Newberg, H. J., & Cole, N. (2009). Robust Asynchronous Optimization for Volunteer Computing Grids. 2009 Fifth IEEE International Conference on E-Science (pp. 263-270). Oxford, United Kingdom. doi:10.1109/e-Science.2009.44

Desell, T., Szymanski, B. K., & Varela, C. A. (2008). An Asynchronous Hybrid Genetic-Simplex Search for Modeling the Milky Way Galaxy Using Volunteer Computing. Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation - GECCO â??08 (p. 921). Atlanta, GA, USA. doi:10.1145/1389095.1389273

Desell, T., Szymanski, B. K., & Varela, C. A. (2008). Asynchronous Genetic Search for Scientific Modeling on Large-Scale Heterogeneous Environments. 2008 IEEE International Symposium on Parallel and Distributed Processing (pp. 1-12). Miami, FL, USA. doi:10.1109/IPDPS.2008.4536169

Desell, T., Varela, C. A., Szymanski, B. K., Newberg, H. J., Magdon-Ismail, M., & Anderson, D. P. (2009). Asynchronous Global Optimization for Massive-Scale Computing. Rensselaer Polytechnic Institute, Troy, NY. Retrieved from http://digitool.rpi.edu:8881/R/PANU21U2G4PKQXIGIIVX1BE5JPCLQDGKI9EX3M2B7VGYK9XAS8-00104?func=dbin-jump-full&object_id=21174&local_base=GEN01&pds_handle=GUEST

Desell, T., Waters, A., Magdon-Ismail, M., Szymanski, B. K., Varela, C. A., Newby, M., Newberg, H. J., et al. (2010). Accelerating the MilkyWay@Home Volunteer Computing Project with GPUs. In R. Wyrzykowski, J. Dongarra, K. Karczewski, & J. Wasniewski (Eds.), Parallel Processing and Applied Mathematics (Vol. 6067, pp. 276-288). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-14390-8_29

Szymanski, B. K., Desell, T., & Varela, C. A. (2008). The Effects of Heterogeneity on Asynchronous Panmictic Genetic Search. In R. Wyrzykowski, J. Dongarra, K. Karczewski, & J. Wasniewski (Eds.), Parallel Processing and Applied Mathematics (Vol. 4967, pp. 457-468). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-540-68111-3_48

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Muon (teilweise in Yoyo@home gelaufen)

Brooks, S. (2010). Muon capture schemes for the neutrino factory. PhD Thesis.

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NanoHive@Home

Allis DG, Drexler EK. (2005). Design and Analysis of a Molecular Tool for Carbon Transfer in Mechanosynthesis. Journal of Computational and Theoretical Nanoscience, Volume 2, Number 1, March 2005, pp. 45-55(11).

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Pancreatic Cancer Research

Richards WG (2002). Virtual screening using grid computing: the screensaver project. Nat Rev Drug Discov. 2002 Jul;1(7):551-5.

Davies EK, Glick M, Harrison KN, Richards WG. (2002). Pattern recognition and massively distributed computing. J Comput Chem. 2002 Dec;23(16):1544-50.

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POEM@Home

Siehe hier.

Predictor@home

Im W, Brooks CL 3rd. (2005). Interfacial folding and membrane insertion of designed peptides studied by molecular dynamics simulations. Proc Natl Acad Sci U S A. 2005 May 10;102(19):6771-6. Epub 2005 Apr 28.

Proteins@home

Schmidt Am Busch M, Lopes A, Mignon D, Simonson T. (2005). Computational protein design: Software implementation, parameter optimization, and performance of a simple model. J Comput Chem. 2007 Dec 10 [Epub ahead of print.]

Schmidt am Busch MS, Lopes A, Amara N, Bathelt C, Simonson T. (2008). Testing the Coulomb/Accessible Surface Area solvent model for protein stability, ligand binding, and protein design. BMC Bioinformatics. 2008 Mar 13;9:148.

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PS3GRID-GPUGRID

Buch, I., Giorgino, T., & De Fabritiis, G. (2011). Complete Reconstruction of an Enzyme-Inhibitor Binding Process by Molecular Dynamics Simulations. Proceedings of the National Academy of Sciences, 108(25), 10184-10189. doi:10.1073/pnas.1103547108

Buch, I., Harvey, M. J., Giorgino, T., Anderson, D. P., & De Fabritiis, G. (2010). High-Throughput All-Atom Molecular Dynamics Simulations Using Distributed Computing. Journal of Chemical Information and Modeling, 50(3), 397-403. doi:10.1021/ci900455r

Buch, I., Sadiq, S. K., & De Fabritiis, G. (2011). Optimized Potential of Mean Force Calculations for Standard Binding Free Energies. Journal of Chemical Theory and Computation, 7(6), 1765-1772. doi:10.1021/ct2000638

De Fabritiis, G., Coveney, P. V., & Villà-Freixa, J. (2008). Energetics of K+ Permeability Through Gramicidin A by Forward-Reverse Steered Molecular Dynamics. Proteins, 73(1), 185-194. doi:10.1002/prot.22036

Giorgino, T., & De Fabritiis, G. (2011). A High-Throughput Steered Molecular Dynamics Study on the Free Energy Profile of Ion Permeation Through Gramicidin A. Journal of Chemical Theory and Computation, 7(6), 1943-1950. doi:10.1021/ct100707s

Giupponi, G., Harvey, M. J., & De Fabritiis, G. (2008). The Impact of Accelerator Processors for High-Throughput Molecular Modeling and Simulation. Drug Discovery Today, 13, 1052-1058. doi:10.1016/j.drudis.2008.08.001

Giupponi, G., Villà-Freixa, J., Harvey, M. J., & De Fabritiis, G. (2007). PS3GRID.NET: A Distributed Computing Environment for Molecular Simulations on the PlayStation 3. International Symposium of Biomedical Informatics. Barcelona, Spain. Retrieved from http://www.ps3grid.net/pub/PS3GRID.pdf

Harvey, M. J., Giupponi, G., Villà-Freixa, J., De Fabritiis, G., & Weber, M. H. W. (n.d.). PS3GRID.NET: Building a Distributed Supercomputer Using the PlayStation 3. Distributed & Grid Computing - Science Made Transparent for Everyone. Principles, Applications and Supporting Communities. In Press. Retrieved from http://www.ps3grid.net/pub/ps3grid_chapter.pdf

Sadiq, S. K., & De Fabritiis, G. (2010). Explicit Solvent Dynamics and Energetics of HIV-1 Protease Flap Opening and Closing. Proteins, 78(14), 2873-2885. doi:10.1002/prot.22806

Selent, J., Sanz, F., Pastor, M., & De Fabritiis, G. (2010). Induced Effects of Sodium Ions on Dopaminergic G-Protein Coupled Receptors. PLoS Computational Biology, 6(8), e1000884. doi:journal.pcbi.1000884

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QMC@home

Korth, M. (2006). Massive parallel Quantum Chemistry: Quantum Monte Carlo at Home. 2nd Pangalactic BOINC Workshop. Geneva, Switzerland. Retrieved from http://qah.uni-muenster.de/mkorth_genf.pdf

Korth, M., Lüchow, A., & Grimme, S. (2008). Toward the Exact Solution of the Electronic Schrödinger Equation for Noncovalent Molecular Interactions: Worldwide Distributed Quantum Monte Carlo Calculations. The Journal of Physical Chemistry A, 112(10), 2104-2109. doi:10.1021/jp077592t

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Quake-Catcher Network

Cochran, E. S., Lawrence, J. F., Christensen, C., & Jakka, R. S. (2009). The Quake-Catcher Network: Citizen Science Expanding Seismic Horizons. Seismological Research Letters, 80(1), 26-30. doi:10.1785/gssrl.80.1.26

Vance, E. (2008). Laptops track Earth's shakes, rattles and rolls. Nature, 452(7186), 397. doi:10.1038/452397a (kein PDF)

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The Ramanujan Machine Project

URL zur Projektpublikationsseite

Rosetta@home

Anindya Roy et al (2023). De novo design of highly selective miniprotein inhibitors of integrins αvβ6 and αvβ8. bioRxiv 2023.06.12.544624; DOI:10.1101/2023.06.12.544624.

Wu, K., Bai, H., Chang, YT. et al (2023). De novo design of modular peptide-binding proteins by superhelical matching. Nature 616, 581–589 (2023). DOI:10.1038/s41586-023-05909-9.

David E. Kim et al (2023). De novo design of small beta barrel proteins. PNAS. 120:11. DOI:10.1073/pnas.2207974120.

Stephen A. Rettie et al (2023). Cyclic peptide structure prediction and design using AlphaFold. bioRxiv 2023.02.25.529956; DOI:10.1101/2023.02.25.529956.

Chidyausiku, T.M., Mendes, S.R., Klima, J.C. et al. (2022). De novo design of immunoglobulin-like domains. Nat Commun. 13, 5661 (2022). DOI:10.1038/s41467-022-33004-6.

Gaurav Bhardwaj et al (2022). Accurate de novo design of membrane-traversing macrocycles. Cell. 185:19, P3520-3532.e26, September 15, 2022. DOI:10.1016/j.cell.2022.07.019

Courbet, A., J. Hansen, Y. Hsia et al. (2022). Computational design of mechanically coupled axle-rotor protein assemblies. Science, 21 Apr 2022, Vol 376, Issue 6591, pp. 383-390. DOI:10.1126/science.abm1183.

Norn, Christoffer, Basile I. M. Wicky, David Juergens et al. (2021). Protein sequence design by conformational landscape optimization. Proc Natl Acad Sci U S A. 2021 Mar 16;118(11):e2017228118. DOI:10.1073/pnas.2017228118.

Hsia, Y., Mout, R., Sheffler, W. et al. (2021). Design of multi-scale protein complexes by hierarchical building block fusion. Nat Commun 12, 2294 (2021). DOI:10.1038/s41467-021-22276-z.

Brunette, Tj, Matthew J. Bick, Jesse M. Hansen, Cameron M. Chow, Justin M. Kollman and David Baker (2020). Modular repeat protein sculpting using rigid helical junctions. Proceedings of the National Academy of Sciences, 117 (16) 8870-8875 (2020). DOI:10.1073/pnas.1908768117.

Mulligan, VK, Kang, CS, Sawaya, MR, et al. (2020). Computational design of mixed chirality peptide macrocycles with internal symmetry. Protein Science. 2020; 29: 2433– 2445. DOI:10.1002/pro.3974.

Wei, Kathy Y., Danai Moschidi, Matthew J. Bick et al. (2020). Computational design of closely related proteins that adopt two well-defined but structurally divergent folds. Proc Natl Acad Sci U S A. 2020 Mar 31;117(13):7208-7215. Epub 2020 Mar 18. DOI:10.1073/pnas.1914808117.

Koehler Leman J, Weitzner BD, Renfrew PD, Lewis SM, Moretti R, Watkins AM, et al. (2020). Better together: Elements of successful scientific software development in a distributed collaborative community. PLoS Comput Biol 16(5): e1007507. DOI:10.1371/journal.pcbi.1007507..

Chen, Z., Boyken, S.E., Jia, M. et al (2019). Programmable design of orthogonal protein heterodimers. Nature 565, 106–111 (2019). DOI:10.1038/s41586-018-0802-y.

Parisa Hosseinzadeh et al. (2018). Comprehensive computational design of ordered peptide macrocycles. Science 358,1461-1466(2017). DOI:10.1126/science.aap7577.

Aaron Chevalier et al (2017). Massively parallel de novo protein design for targeted therapeutics. Nature. 2017 Oct 5;550(7674):74-79. DOI:10.1038/nature23912. Epub 2017 Sep 27.

Gabriel J. Rocklin et al. (2017). Global analysis of protein folding using massively parallel design, synthesis, and testing. Science 357,168-175(2017). DOI:10.1126/science.aan0693.

Sergey Ovchinnikov et al. (2017). Protein structure determination using metagenome sequence data. Science 355,294-298(2017). DOI:10.1126/science.aah4043.

Ovchinnikov, S., Kim, D.E., Wang, R.Y.-R., Liu, Y., DiMaio, F. and Baker, D. (2016). Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta. Proteins, 84: 67-75. DOI:10.1002/prot.24974.

Shoshana J Wodak (2012). Next-generation protein engineering targets influenza

Malmstrom L, Riffle M, Strauss CE, Chivian D, Davis TN, Bonneau R, Baker D. (2007). Superfamily Assignments for the Yeast Proteome through Integration of Structure Prediction with the Gene Ontology. PLoS Biol. 2007 Mar 20;5(4):e76 [Epub ahead of print.]

Yarov-Yarovoy V, Schonbrun J, Baker D. (2006). Multipass membrane protein structure prediction using Rosetta. Proteins. 2006 Mar 1;62(4):1010-25.

Misura KM, Chivian D, Rohl CA, Kim DE, Baker D. (2006). Physically realistic homology models built with ROSETTA can be more accurate than their templates. Proc Natl Acad Sci U S A. 2006 Apr 4;103(14):5361-6. Epub 2006 Mar 27.

Yarov-Yarovoy V, Baker D, Catterall WA. (2006). Voltage sensor conformations in the open and closed states in ROSETTA structural models of K(+) channels. Proc Natl Acad Sci U S A. 2006 May 9;103(19):7292-7. Epub 2006 Apr 28.

Wollacott AM, Zanghellini A, Murphy P, Baker D. (2007). Prediction of structures of multidomain proteins from structures of the individual domains. Protein Sci. 2007 Feb;16(2):165-75. Epub 2006 Dec 22.

Bradley P, Malmstrom L, Qian B, Schonbrun J, Chivian D, Kim DE, Meiler J, Misura KM, Baker D. (2005). Free modeling with Rosetta in CASP6. Proteins. 2005;61 Suppl 7:128-34.

Chivian D, Kim DE, Malmstrom L, Schonbrun J, Rohl CA, Baker D. (2005). Prediction of CASP6 structures using automated Robetta protocols. Proteins. 2005;61 Suppl 7:157-66.

Kim DE, Chivian D, Malmstrom L, Baker D. (2005). Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM. Proteins. 2005;61 Suppl 7:193-200.

Lacy DB, Lin HC, Melnyk RA, Schueler-Furman O, Reither L, Cunningham K, Baker D, Collier RJ. (2005). A model of anthrax toxin lethal factor bound to protective antigen. Proc Natl Acad Sci U S A. 2005 Nov 8;102(45):16409-14. Epub 2005 Oct 26.

Rohl CA, Strauss CE, Misura KM, Baker D. (2004). Protein structure prediction using Rosetta. Methods Enzymol. 2004;383:66-93.

Kuhn M, Meiler J, Baker D. (2004). Strand-loop-strand motifs: prediction of hairpins and diverging turns in proteins. Proteins. 2004 Feb 1;54(2):282-8.

Rohl CA, Strauss CE, Chivian D, Baker D. (2004). Modeling structurally variable regions in homologous proteins with rosetta. Proteins. 2004 May 15;55(3):656-77.

Kim DE, Chivian D, Baker D. (2004). Protein structure prediction and analysis using the Robetta server. Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W526-31.

Misura KM, Morozov AV, Baker D. (2004). Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction. J Mol Biol. 2004 Sep 10;342(2):651-64.

Bradley P, Chivian D, Meiler J, Misura KM, Rohl CA, Schief WR, Wedemeyer WJ, Schueler-Furman O, Murphy P, Schonbrun J, Strauss CE, Baker D. (2003). Rosetta predictions in CASP5: successes, failures, and prospects for complete automation. Proteins. 2003;53 Suppl 6:457-68.

Chivian D, Kim DE, Malmstrom L, Bradley P, Robertson T, Murphy P, Strauss CE, Bonneau R, Rohl CA, Baker D. (2003). Automated prediction of CASP-5 structures using the Robetta server. Proteins. 2003;53 Suppl 6:524-33.

Schueler-Furman O, Baker D. (2003). Conserved residue clustering and protein structure prediction. Proteins. 2003 Aug 1;52(2):225-35.

Kinch LN, Baker D, Grishin NV. (2003). Deciphering a novel thioredoxin-like fold family. Proteins. 2003 Aug 15;52(3):323-31.

Tsai J, Bonneau R, Morozov AV, Kuhlman B, Rohl CA, Baker D. (2003). An improved protein decoy set for testing energy functions for protein structure prediction. Proteins. 2003 Oct 1;53(1):76-87.

Sadreyev RI, Baker D, Grishin NV. (2003). Profile-profile comparisons by COMPASS predict intricate homologies between protein families. Protein Sci. 2003 Oct;12(10):2262-72.

Meiler J, Baker D. (2003). Coupled prediction of protein secondary and tertiary structure. Proc Natl Acad Sci U S A. 2003 Oct 14;100(21):12105-10. Epub 2003 Oct 3.

Wedemeyer WJ, Baker D. (2003). Efficient minimization of angle-dependent potentials for polypeptides in internal coordinates. Proteins. 2003 Nov 1;53(2):262-72.

Meiler J, Baker D. (2003). Rapid protein fold determination using unassigned NMR data. Proc Natl Acad Sci U S A. 2003 Dec 23;100(26):15404-9. Epub 2003 Dec 10.

Rohl CA, Baker D. (2002). De novo determination of protein backbone structure from residual dipolar couplings using Rosetta. J Am Chem Soc. 2002 Mar 20;124(11):2723-9.

Ruczinski I, Kooperberg C, Bonneau R, Baker D. (2002). Distributions of beta sheets in proteins with application to structure prediction. Proteins. 2002 Jul 1;48(1):85-97.

Bonneau R, Ruczinski I, Tsai J, Baker D. (2002). Contact order and ab initio protein structure prediction. Protein Sci. 2002 Aug;11(8):1937-44.

Bonneau R, Strauss CE, Rohl CA, Chivian D, Bradley P, Malmstrom L, Robertson T, Baker D. (2002). De novo prediction of three-dimensional structures for major protein families. J Mol Biol. 2002 Sep 6;322(1):65-78.

Saunders CT, Baker D. (2002). Evaluation of structural and evolutionary contributions to deleterious mutation prediction. J Mol Biol. 2002 Sep 27;322(4):891-901.

Bonneau R, Tsai J, Ruczinski I, Chivian D, Rohl C, Strauss CE, Baker D. (2001). Rosetta in CASP4: progress in ab initio protein structure prediction. Proteins. 2001;Suppl 5:119-26.

Lee MR, Baker D, Kollman PA. (2001). 2.1 and 1.8 A average C(alpha) RMSD structure predictions on two small proteins, HP-36 and s15. J Am Chem Soc. 2001 Feb 14;123(6):1040-6.

Simons KT, Strauss C, Baker D. (2001). Prospects for ab initio protein structural genomics. J Mol Biol. 2001 Mar 9;306(5):1191-9.

Bonneau R, Strauss CE, Baker D. (2001). Improving the performance of Rosetta using multiple sequence alignment information and global measures of hydrophobic core formation. Proteins. 2001 Apr 1;43(1):1-11.

Lee MR, Tsai J, Baker D, Kollman PA. (2001). Molecular dynamics in the endgame of protein structure prediction. J Mol Biol. 2001 Oct 19;313(2):417-30.

Bowers PM, Strauss CE, Baker D. (2000) De novo protein structure determination using sparse NMR data. J Biomol NMR. 2000 Dec;18(4):311-8.

Simons KT, Bonneau R, Ruczinski I, Baker D. (1999). Ab initio protein structure prediction of CASP III targets using ROSETTA. Proteins. 1999;Suppl 3:171-6.

Mehr...

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SETI@home

Anderson, D. P., Cobb, J., Korpela, E., Lebofsky, M., & Werthimer, D. (2002). SETI@Home: an Experiment in Public-Resource Computing. Communications of the ACM, 45(11), 56-61. doi:10.1145/581571.581573

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Seventeen or bust

Helm, L., Moore, P., Samidoost, P., & Woltman, G. (2008). Resolution of the Mixed Sierpinski Problem. Integers: Electronic Journal of Combinatorial Number Theory, 8, A61.

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SIMAP

Arnold, R., Rattei, T., Tischler, P., Truong, M.-D., Stumpflen, V., & Mewes, H.-W. (2005). SIMAP--The Similarity Matrix of Proteins. Bioinformatics, 21, ii42-ii46. doi:10.1093/bioinformatics/bti1107

Rattei, T., Arnold, R., Tischler, P., Lindner, D., Stumpflen, V., & Mewes, H.-W. (2006). SIMAP: the Similarity Matrix of Proteins. Nucleic Acids Research, 34(90001), D252-D256. doi:10.1093/nar/gkj106

Rattei, T., Tischler, P., Arnold, R., Hamberger, F., Krebs, J., Krumsiek, J., Wachinger, B., et al. (2007). SIMAP Structuring the Network of Protein Similarities. Nucleic Acids Research, 36, D289-D292. doi:10.1093/nar/gkm963

Rattei, T., Tischler, P., Goetz, S., Jehl, M.-A., Hoser, J., Arnold, R., Conesa, A., et al. (2009). SIMAP--a Comprehensive Database of Pre-Calculated Protein Sequence Similarities, Domains, Annotations and Clusters. Nucleic Acids Research, 38, D223-D226. doi:10.1093/nar/gkp949

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Spinhenge@home

Schröder, C., Prozorov, R., Kögerler, P., Vannette, M. D., Fang, X., Luban, M., Matsuo, A., et al. (2008). Multiple Nearest-Neighbor Exchange Model for the Frustrated Magnetic Molecules Mo72Fe30 and Mo72Cr30. Physical Review B, 77(22), 4409-4417. doi:10.1103/PhysRevB.77.224409 arXiv:0801.2065v1

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TANPAKU

Huber, G. A., & Kim, S. (1996). Weighted-ensemble Brownian dynamics simulations for protein association reactions. Biophysical Journal, 70(1), 97-110. doi:10.1016/S0006-3495(96)79552-8

Rojnuckarin, A., Kim, S., & Subramaniam, S. (1998). Brownian dynamics simulations of protein folding: access to milliseconds time scale and beyond. Proceedings of the National Academy of Sciences of the United States of America, 95(8), 4288-4292. PMID:9539729

Rojnuckarin, A., Livesay, D. R., & Subramaniam, S. (2000). Bimolecular reaction simulation using Weighted Ensemble Brownian dynamics and the University of Houston Brownian Dynamics program. Biophysical Journal, 79(2), 686-693. doi:10.1016/S0006-3495(00)76327-2

Ando, T., Meguro, T., & Yamato, I. (2002). Development of an Atomistic Brownian Dynamics Algorithm with Implicit Solvent Model for Long Time Simulation. Journal of Computational Chemestry Japan, 1(3), 115-122. Retrieved from http://www.sccj.net/publications/JCCJ/v1n3/a16/document.pdf

Meguro, T., Ando, T., & Yamato, I. (2003). Development of Multifunctional Object-Oriented Program Library for Molecular Simulation and Structure Analysis. Journal of Computational Chemestry Japan, 2(1), 7-16. Retrieved from http://www.sccj.net/publications/JCCJ/v2n1/a12/document.pdf

Ando, T., Meguro, T., & Yamato, I. (2003). Multiple Time Step Brownian Dynamics for Long Time Simulation of Biomolecules. Molecular Simulation, 29(8), 471-478. doi:10.1080/0892702031000120528

Ando, T., Meguro, T., & Yamato, I. (2004). A New Implicit Solvent Model for Brownian Dynamics Simulation: Solvent-Accessible Surface Area Dependent Effective Charge Model. Journal of Computational Chemestry Japan, 3(4), 129-136. Retrieved from http://www.sccj.net/publications/JCCJ/v3n4/a12/document.pdf

Ando, T., & Yamato, I. (2005). Free Energy Landscapes of Two Model Peptides: α-Helical and β-Hairpin Peptides Explored with Brownian Dynamics Simulation. Molecular Simulation, 31(10), 683-693. doi:10.1080/08927020500183257

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TN-Grid

Gene@home

Discovering Causal Relationships in Grapevine Expression Data to Expand Gene Networks. A Case Study: Four Networks Related to Climate Change Giulia Malacarne1†, Stefania Pilati1†, Samuel Valentini2†, Francesco Asnicar3, Marco Moretto2, Paolo Sonego2, Luca Masera3, Valter Cavecchia4, Enrico Blanzieri3,4 and Claudio Moser1* (2018). Discovering Causal Relationships in Grapevine Expression Data to Expand Gene Networks. A Case Study: Four Networks Related to Climate Change. frontienrs in Plant Science. doi:10.3389/fpls.2018.01385

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Virtual Prairie

Garbey, M. (2008). Virtual Prairies with BOINC. 4. Pan-Galactic BOINC Workshop. Grenoble, France. Retrieved from http://vcsc.cs.uh.edu/virtual-prairie/pages_site_aurelie/Grenoble.pdf

Garbey, M., Mony, Cendrine, & Smaoui, M. (2008). Fluid Flow - Agent Based Hybrid Model for the Simulation of Virtual Prairies. Proceedings of the Parallel Computing Fluid Dynamics Conference. Lyon, France. Retrieved from http://vcsc.cs.uh.edu/virtual-prairie/pages_site_aurelie/ParCFD4.pdf

Mony, Ce, & Garbey, M. (2009). Updates on the Virtual Prairie Project. 5. Pan-Galactic BOINC Workshop. Barcelona, Spain. Retrieved from http://vcsc.cs.uh.edu/virtual-prairie/pages_site_aurelie/Boinc_workshop_Marc_Garbey_2.pdf

Mony, Cendrine, Garbey, M., & Smaoui, M. (2008). Using Modelling to Understand Clonal Strategies in Optimal Growing Conditions. 51. Annual Symposium of the International Association for Vegetation Science. South Africa.

Mony, Cendrine, Garbey, M., Smaoui, M., & Benot, M. L. (2010). Large Scale Parameter Study of an Individual-Based Model of Clonal Plant with Volunteer Computing. Ecological Modelling, 222, 935-946. doi:10.1016/j.ecolmodel.2010.10.014

Smaoui, M., Garbey, M., & Mony, Cendrine. (2008). Virtual Prairie: Going Green with Volunteer Computing. Proceedings of IEEE Asia-Pacific Services Computing Conference (pp. 427-434). Yilan, Taiwan. Retrieved from http://vcsc.cs.uh.edu/virtual-prairie/pages_site_aurelie/APSCC-VirtualPrairie.pdf

Smaoui, M., Nguyen, V. H., & Garbey, M. (2009). Parallel Genetic Algorithm Implementation for BOINC. Proceedings of the International Conference on Parallel Computing. Lyon, France. Retrieved from http://vcsc.cs.uh.edu/virtual-prairie/pages_site_aurelie/ParCo09Smaoui_Garbey.pdf

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World Community Grid

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Fight AIDS At Home (FAAH)

Chang, M. W., Lindstrom, W., Olson, A. J., & Belew, R. K. (2007). Analysis of HIV Wild-Type and Mutant Structures Via in Silico Docking Against Diverse Ligand Libraries. Journal of Chemical Information and Modeling, 47(3), 1258-1262. doi:10.1021/ci700044s

Computing For Clean Water (CFCW)

Ma, M. D., Shen, L., Sheridan, J., Liu, J. Z., Chen, C., & Zheng, Q. (2011). Friction of Water Slipping in Carbon Nanotubes. Physical Review E, 83(3), 36316. APS. doi:10.1103/PhysRevE.83.036316

Help Conquer Cancer (HCC)

Cumbaa, C. A., & Jurisica, I. (2010). Protein Crystallization Analysis on the World Community Grid. Journal of Structural and Functional Genomics, 11(1), 61-69. doi:10.1007/s10969-009-9076-9

Help Cure Muscular Dystrophy (HCMD)

Bertis, V., Bolze, R., Desprez, F., & Reed, K. (2008). Large Scale Execution of a Bioinformatic Application on a Volunteer Grid. IEEE International Symposium on Parallel and Distributed Processing, 2008. IPDPS 2008 (pp. 1-8). doi:10.1109/IPDPS.2008.4536484

Bertis, V., Bolze, R., Desprez, F., & Reed, K. (2009). From Dedicated Grid to Volunteer Grid: Large Scale Execution of a Bioinformatics Application. Journal of Grid Computing, 7(4), 463-478. Springer. doi:10.1007/s10723-009-9130-7

Bolze, R. (2008). Analyse et déploiement de solutions algorithmiques et logicielles pour des applications bioinformatiques à grande échelle sur la grille. Ecole normale supérieure de Lyon. Retrieved from http://tel.archives-ouvertes.fr/tel-00344249/en/

Engelen, S., Trojan, L. A., Sacquin-Mora, S., Lavery, R., & Carbone, A. (2009). Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling. PLoS Computational Biology, 5(1), e1000267. doi:10.1371/journal.pcbi.1000267

Sacquin-Mora, S., Carbone, A., & Lavery, R. (2008). Identification of Protein Interaction Partners and Protein--Protein Interaction Sites. Journal of Molecular Biology, 382(5), 1276-1289. doi:10.1016/j.jmb.2008.08.002

Help Defeat Cancer (HDC)

Chen, W., Foran, D. J., & Reiss, M. (2002). Unsupervised imaging, registration and archiving of tissue microarrays. Proceedings of the Annual American Medical Informatics Association Symposium. AMIA Symposium, 136-139. PMID:12463802

Chen, W., Reiss, M., & Foran, D. J. (2004). A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics. IEEE Transactions on Information Technology in Biomedicine, 8(2), 89-96. doi:10.1109/TITB.2004.828891

Foran, D. J., Yang, L., Chen, W., Hu, J., Goodell, L. A., Reiss, M., Wang, F., et al. (2011). ImageMiner: a Software System for Comparative Analysis of Tissue Microarrays Using Content-Based Image Retrieval, High-Performance Computing, and Grid Technology. Journal of the American Medical Informatics Associatio, 18(4), 403-415. doi:10.1136/amiajnl-2011-000170

Hall, B., Chen, W., Reiss, M., & Foran, D. J. (2007). A Clinically Motivated 2-Fold Framework for Quantifying and Classifying Immunohistochemically Stained Specimens. International Conference on Medical Image Computing and Computer-Assisted Intervention. MICCAI, 10, 287-294. PMID:18044580

Schmidt, C., Parashar, M., Chen, W., & Foran, D. J. (2007). Engineering a Peer-to-Peer Collaboratory for Tissue Microarray Research. Second International Workshop on Challenges of Large Applications in Distributed Environments. Honolulu, Hawaii. doi:10.1109/CLADE.2004.1309093

Yang, L., Chen, W., Meer, P., Salaru, G., Feldman, M. D., & Foran, D. J. (2007). High Throughput Analysis of Breast Cancer Specimens on the Grid. International Conference on Medical Image Computing and Computer-Assisted Intervention. MICCAI, 10, 617-625. Retrieved from http://pleiad.umdnj.edu/IBM/pdfs/Yang_et_al_miccai07.pdf

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Human Proteome Folding Project (HPFP)

Bonneau, R., Facciotti, M. T., Reiss, D. J., Schmid, A. K., Pan, M., Kaur, A., Thorsson, V., et al. (2007). A Predictive Model for Transcriptional Control of Physiology in a Free Living Cell. Cell, 131(7), 1354-1365. doi:10.1016/j.cell.2007.10.053

Boxem, M., Maliga, Z., Klitgord, N., Li, N., Lemmens, I., Mana, M., De Lichtervelde, L., et al. (2008). A Protein Domain-Based Interactome Network for C. Elegans Early Embryogenesis. Cell, 134(3), 534-545. doi:10.1016/j.cell.2008.07.009

Drew, K., Winters, P., Butterfoss, G. L., Berstis, V., Uplinger, K., Armstrong, J., Riffle, M., et al. (2011). The proteome folding project: Proteome-scale prediction of structure and function. Genome Research. doi:10.1101/gr.121475.111

Malmström, L., Riffle, M., Strauss, C. E. M., Chivian, D., Davis, T. N., Bonneau, R., & Baker, D. (2007). Superfamily Assignments for the Yeast Proteome Through Integration of Structure Prediction with the Gene Ontology. PLoS Biology, 5(4), e76. doi:10.1371/journal.pbio.0050076

Pentony, M. M., Winters, P., Penfold-Brown, D., Drew, K., Narechania, A., DeSalle, R., Bonneau, R., & Purugganan, M. D. (2012). The Plant Proteome Folding Project: Structure and Positive Selection in Plant Protein Families. Genome Biol Evol, 4 (3): 360-371. doi:10.1093/gbe/evs015

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Microbiome Immunity Project (MIP)

Koehler Leman, J., Szczerbiak, P., Renfrew, P.D. et al. (2023). Sequence-structure-function relationships in the microbial protein universe. Nat Commun 14, 2351. doi:10.1038/s41467-023-37896-w

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Nutritious Rice for the World (NRW)

Hung, L.-H., Guerquin, M., & Samudrala, R. (2011). GPU-QJ, a Fast Method for Calculating Root Mean Square Deviation (RMSD) After Optimal Superposition. BMC Research Notes, 4(97). doi:10.1186/1756-0500-4-97

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The Clean Energy Project (TCEP)

Hachmann, J., Olivares-Amaya, R., Atahan-Evrenk, S., Amador-Bedolla, C., Sánchez-Carrera, R. S., Gold-Parker, A., Vogt, L., et al. (2011). The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid. The Journal of Physical Chemistry Letters, 2(17), 2241-2251. doi:10.1021/jz200866s

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XANSONS for COD

Neverov, V.S. & Khrapov, N.P. (2018). “XANSONS for COD”: a new small BOINC project in crystallography. Open Engineering. DOI: 10.1515/eng-2018-0014.

Neverov, V.S. (2017) XaNSoNS: GPU-accelerated simulator of diffraction patterns of nanoparticles. SoftwareX. DOI: 10.1016/j.softx.2017.01.004.

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Yoyo@home

Siehe #EulerNet, #Evolution@home, #Harmonious Trees und #Muon.

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