Publications by BOINC projects

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Science research projects typically publish their results in scientific journals. Preliminary results are often published in conferences. In the academic world, the scientific contribution of a project is measured largely by the number of its publications, and the prestige of the journals and conferences in which they appear (high-prestige journals include Nature, Science, and PNAS).

We encourage BOINC volunteers to support projects that make a major scientific contribution. Keep in mind that doing research and publishing papers may take several years, so newer projects will naturally have few or no publications.

The following scientific papers have resulted from BOINC-based projects (this list does not include papers about volunteer computing or about BOINC itself; those are here).

Climateprediction.net

  1. James Murphy, David Sexton, David Barnett, Gareth Jones, Mark Webb, Matthew Collins & David Stainforth, Quantification of modelling uncertainties in a large ensemble of climate change simulations, Nature, 430, pp. 768-772, August 2004.
  2. D. A. Stainforth, T. Aina, C. Christensen, M. Collins, N. Faull, D. J. Frame, J. A. Kettleborough, S. Knight, A. Martin, J. M. Murphy, C. Piani, D. Sexton, L. A. Smith, R. A. Spicer, A. J. Thorpe & M. R. Allen, Uncertainty in predictions of the climate response to rising levels of greenhouse gases, Nature, 433, pp. 403-406, January 2005.
  3. D. J. Frame, B. B. B. Booth, J. A. Kettleborough, D. A. Stainforth, J. M. Gregory, M. Collins, and M. R. Allen, Constraining climate forecasts: The role of prior assumptions, Geophysical Review Letters, 32, May 2005.
  4. C. Piani, D. J. Frame, D. A. Stainforth, and M. R. Allen, Constraints on climate change from a multi-thousand member ensemble of simulations, Geophysical Review Letters, 32, December 2005.
  5. P. Pall, M.R. Allen, D.A. Stone, Testing the Clausius-Clapeyron constraint on changes in extreme precipitation under CO2 warming. Climate Dynamics, 23:4, pp. 351-363, August 2006.
  6. M. Collins and S. Knight (Eds.), Ensembles and probabilities: a new era in the prediction of climate change, Phil. Trans. R. Soc. A, Print: 1364-503X, Online: 1471-2962, 2007.
  7. C.G. Knight, S.H.E. Knight, N. Massey, T. Aina, C. Christensen, D.J. Frame, J.A. Kettleborough, A. Martin, S. Pascoe, B. Sanderson, D.A. Stainforth, M.R. Allen, Association of parameter, software and hardware variation with large scale behavior across 57,000 climate models, PNAS, July 2007.
  8. B. M. Sanderson, R. Knutti, T. Aina, C. M. Christensen, N. E. Faull, D. J. Frame, W. J. Ingram, C. Piani, D. A. Stainforth, D. A. Stone and M. R. Allen. Constraints on model response to greenhouse gas forcing and the role of sub-grid scale processes, Journal of Climate, in press, 2007.
  9. C. Piani, T. Aina, C. Christensen, D. Frame, N. Faull and M. Allen. Regional probabilistic climate forecasts from a multi-thousand, multi-model ensemble of simulations, Journal of Geophysical Research, accepted, 2007.
  10. D. J. Frame, N. E. Faull, M. M. Joshi & M. R. Allen, Probabilistic climate forecasts and inductive problems, Philosophical Transactions of the Royal Society A, 2007.
  11. D. Ackerley, E. J. Highwood, and D. J. Frame, Quantifying the effects of perturbing the physics of an interactive sulfur scheme using an ensemble of GCMs on the climateprediction.net platform, J. Geophys. Res., 114, D01203, January 2009.
  12. D.J. Frame, T. Aina, C.M. Christensen, N. E. Fall, S.H.E. Knight, C. Piani, S.M. Rosier, K. Yamazaki, Y. Yamazaki and M.R. Allen, The climateprediction.net BBC climate change experiment: design of the coupled model ensemble, Philosophical Transactions of The Royal Society A, 367, pp.855-870, 2009.
  13. H. Fowler, D. Cooley, S. Sain and M. Thurston, Detecting change in UK extreme precipitation using results from the climateprediction.net BBC climate change experiment, 2010, Extremes DOI 10.1007/s10687-010-0101-y.
  14. Pardeep Pall, Tolu Aina, Dáithí A. Stone, Peter A. Stott, Toru Nozawa, Arno G. J. Hilberts, Dag Lohmann, Myles R. Allen. Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000. Nature, Volume 470, 382–385 (17 February 2011).

Docking@home

  1. T. Estrada, R. Armen, and M. Taufer: Automatic Selection of Near-Native Protein-Ligand Conformations using a Hierarchical Clustering and Volunteer Computing. In Proceedings of the International Conference On Bioinformatics and Computational Biology (ACM-BCB), August 2010, Niagara Falls, NY, USA.

Einstein@Home

  1. Online Report on the S3 Analysis: http://einstein.phys.uwm.edu/FinalS3Results
  2. Paper on the S4 analysis: Einstein@Home search for periodic gravitational waves in LIGO S4 data, by B. Abbott et al. (the LIGO Scientific Collaboration), Phys. Rev. D 79, 022001 (2009)
  3. Paper on the early S5 analysis: Einstein@Home search for periodic gravitational waves in early S5 LIGO data. Abbott, B.P. et al. (the LIGO Scientific Collaboration) Phys. Rev. D 80, 042003 (2009).
  4. Paper about the first radio pulsar discovery: Pulsar Discovery by Global Volunteer Computing. B. Knispel, B. Allen, J. M. Cordes, J. S. Deneva, D. Anderson et. al. Science 10 September 2010: Vol. 329. no. 5997, p. 1305
  5. Paper about the second radio pulsar discovery: Arecibo PALFA Survey and Einstein@Home: Binary Pulsar Discovery by Volunteer Computing. B. Knispel, P. Lazarus, B. Allen, D. Anderson et. al. Astrophysical Journal Letters 732, p. L1, 2011.

Lattice

  1. Varadan, R., Assfalg, M., Raasi, S., Pickart, C. & Fushman, D. Structural determinants for selective recognition of a Lys48-linked polyubiquitin chain by a UBA domain. Molecular Cell 18, 687-98 (2005).
  2. Grand, J., M. P. Cummings, A. G. Rebelo, T. H. Ricketts, and M. C. Neel. Biased data reduce efficiency and effectiveness of conservation reserve networks. Ecology Letters 10:364-374 (2007).
  3. Tishkoff, S. A., Gonder, M. K., Henn, B. M., Mortensen, H., Knight, A., Gignoux, C., Fernandopulle, N., Lema, G., Nyambo, T. B., Ramakrishnan, U., Reed, F. A. & Mountain, J. L. History of click-speaking populations of Africa inferred from mtDNA and Y chromosome genetic variation. Molecular Biology and Evolution 24:2180-2195 (2007).
  4. Pettengill, J. B., & M. C. Neel. 2008. Phylogenetic patterns and conservation among North American members of the genus Agalinis (Orobanchaceae). BMC Evolutionary Biology 8:264.
  5. Regier, J. C., Zwick, A., Cummings, M. P., Kawahara, A. Y., Cho, S., Weller, S. J., Roe, A. D., Baixeras-Almela, J., Brown, J. W., Parr, C. S., Davis, D. R., Epstein, M. E., Hallwachs, W., Hausmann, A., Janzen, D. H., Kitching, I. J., Solis, M. A., Yen, S.-H., Bazinet, A., & Mitter, C. Toward reconstructing the evolution of advanced moths and butterflies (Lepidoptera: Ditrysia): an initial molecular study. BMC Evolutionary Biology 9:280 (2009).
  6. Regier, J.C., Shultz, J. W., Zwick, A., Hussey, A., Ball, B., Wetzer, R., Martin J. W. & C.W. Cunningham C. W. Arthropod relationships revealed by phylogenomic analysis of nuclear protein-coding sequences. Nature 463:1079-1083 (2010).
  7. Reyna-Fabín, M., Laclette, J. P., Cummings, M. P., Sarma S. S. S., & García-Varela, M. Validating the systematic position of Plationus Segers, Murugan & Dumont, 1993 (Rotifera: Brachionidae) using sequences of the large subunit of the nuclear ribosomal DNA and of cytochrome c oxidase. Hydrobiologia 644:361-370 (2010).
  8. Regier, J.C., Zwick, A. 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 (2011).
  9. Zwick, A, Regier JC, Mitter C, Cummings MP. Increased gene sampling yields robust support for higher-level clades within Bombycoidea (Lepidoptera). Syst Entomol. 36:31–43 (2011).
  10. Kawahara, AY, Ohshima I, Kawakita A, Regier JC, Mitter C, Cummings MP, Davis DR, Wagner DL, De Prinis J, Lopez-Vaamonde C. Increased gene sampling provides stronger support for higher-level groups within gracillariid leaf mining moths and relatives (Lepidoptera: Gracillariidae). BMC Evol Biol. 11:182 (2011).
  11. Cho, S, Zwick A, Regier JC, Mitter C, Cummings MP, Yao J, Du Z, Zhao H, Kawahara AY, Weller S et al. Can deliberately incomplete gene sample augmentation improve a phylogeny estimate for the advanced moths and butterflies (Hexapoda: Lepidoptera)? Syst Biol. In press.

LHC@home

  1. Herr, Werner; Kaltchev, D.I.; McIntosh, E.; Schmidt, F. Large scale beam-beam simulations for the CERN LHC using distributed computing resources. 10th European Particle Accelerator Conference, Edinburgh, UK, 26 - 30 Jun 2006, pp.526
  1. McIntosh, E; Schmidt, F; de Dinechin, F. Massive Tracking On Heterogeneous Platforms. 9th International Computational Accelerator Physics Conference (ICAP), October 2006

malariacontrol.net

  1. Penny MA, Maire N, Studer A, Schapira A, Smith TA. What Should Vaccine Developers Ask? Simulation of the Effectiveness of Malaria Vaccines. PLoS ONE 3(9): e3193. doi:10.1371/journal.pone.0003193 (2008)
  2. Ross A, Penny M, Maire N, Studer A, Carneiro I, Schellenberg D, Greenwood B, Tanner M, Smith T. Modelling the Epidemiological Impact of Intermittent Preventive Treatment against Malaria in Infants. PLoS ONE 3(7): e2661 doi:10.1371/journal.pone.0002661. (2008)
  3. Gosoniu L, Vounatsou P, Sogoba N, Maire N, Smith T. Mapping malaria risk in West Africa using a Bayesian nonparametric non-stationary model. Computational Statistics and Data Analysis 53: 3358-3371. (2009)
  4. Tediosi F, Maire N, Penny MA, Studer A, Smith TA. Simulation of the cost-effectiveness of malaria vaccines. Malaria Journal 2009, 8:127 doi:10.1186/1475-2875-8-127 (2009)
  5. Ross A, Smith TA. Interpreting malaria age-prevalence and incidence curves: a simulation study of the effects of different types of heterogeneity. Malaria Journal 2010, 8:127 doi:10.1186/1475-2875-9-132 (2010)
  6. Carneiro I, Smith L, Ross A, Roca-Feltrer A, Greenwood B, Schellenberg JA, Smith TA, Schellenberg D. Intermittent preventive treatment for malaria in infants: a decision-support tool for sub-Saharan Africa. Bulletin of the World Health Organization 2010;88:807-814. doi: 10.2471/BLT.09.072397 (2010)
  7. Smith TA, Chitnis N, Briët OJ, Tanner M. Uses of mosquito-stage transmission-blocking vaccines against Plasmodium falciparum. Trends Parasitol. 2011 Jan 27. [Epub ahead of print]
  8. Ross A, Maire N, Sicuri E, Smith T, Conteh L. 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 (2011)
  9. Bretscher MT, Maire N, Chitnis N, Felger I, Owusu-Agyei S, Smith T. The distribution of Plasmodium falciparum infection durations. Epidemics 3, 109-118 (2011)
  10. Maire N, Shilcutt SD, Walker DG, Tediosi F, Smith TA. Cost-Effectiveness of the Introduction of a Pre-Erythrocytic Malaria Vaccine into the Expanded Program on Immunization in Sub-Saharan Africa: Analysis of Uncertainties Using a Stochastic Individual-Based Simulation Model of Plasmodium falciparum Malaria. Value in Health 2011, 14:1028–1038
  11. Crowell V, Hardy D, Briet O, Chitnis N, Maire N, Smith T, Can we depend on case management to prevent re-establishment of P. falciparum malaria, after local interruption of transmission?. Epidemics, in press

Milkyway@home

  1. Travis Desell, David P. Anderson, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos A. Varela. An Analysis of Massively Distributed Evolutionary Algorithms. In the Proceedings of the 2010 IEEE Congress on Evolutionary Computation (IEEE CEC 2010), Barcelona, Spain, July 2010. To Appear.
  2. Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos A. Varela, Heidi Newberg and David P. Anderson. Validating Evolutionary Algorithms on Volunteer Computing Grids. In the Proceedings of the 10th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS 2010), Amsterdam, Netherlands, June 2010. To Appear.
  3. Nathan Cole, Travis Desell, Daniel Lombranaa Gonzalez, Francisco Fernandez de Vega, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos Varela. Evolutionary Algorithms on Volunteer Computing Platforms: The MilkyWay@Home Project. In F. Fernandez de Vega, E. Cantu-Paz (Eds.): Parallel and Distributed Computational Intelligence, SCI 269, pp 63-90. Springer-Verlag Berlin Heidelberg. 2010
  4. Travis Desell. Asynchronous Global Optimization for Massive-Scale Computing. PhD thesis. Rensselaer Polytechnic Institute. 2009
  5. Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Heidi Newberg and Nathan Cole. Robust Asynchronous Optimization for Volunteer Computing Grids. In the 5th IEEE International Conference on e-Science (eScience2009), Oxford, UK, pages 263-270, December 2009.
  6. Travis Desell, Anthony Waters, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Matthew Newby, Heidi Newberg, Andreas Przystawik and Dave Anderson. Accelerating the MilkyWay@Home volunteer computing project with GPUs. In 8th International Conference on Parallel Processing and Applied Mathematics (PPAM 2009), Wroclaw, Poland, September 2009. To appear.
  7. Nathan Cole. Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. PhD thesis. Rensselaer Polytechnic Institute. 2009.
  8. Nathan Cole, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Kristopher Dawsey, Warren Hayashi, Jonathan Purnell, Boleslaw Szymanski, Carlos A. Varela, Benjamin Willett, and James Wisniewski. Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. Astrophysical Journal, 683:750-766, 2008.
  9. Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. An Asynchronous Hybrid Genetic-Simplex Search for Modeling the Milky Way Galaxy using Volunteer Computing. In Genetic and Evolutionary Computation Conference (GECCO 2008), Atlanta, Georgia, pages 921-928, July 2008.
  10. Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. Asynchronous Genetic Search for Scientific Modeling on Large-Scale Heterogeneous Environments. In Proceedings of the 17th International Heterogeneity in Computing Workshop (HCW/IPDPS'08), Miami, FL, pages 12pp, April 2008. IEEE.
  11. Boleslaw Szymanski, Travis Desell, and Carlos A. Varela. The Effect of Heterogeneity on Asynchronous Panmictic Genetic Search. In Proc. of the Seventh International Conference on Parallel Processing and Applied Mathematics (PPAM'2007), LNCS, Gdansk, Poland, September 2007.
  12. Travis Desell, Nathan Cole, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski, and Carlos A. Varela. Distributed and Generic Maximum Likelihood Evaluation. In 3rd IEEE International Conference on e-Science and Grid Computing (eScience2007), Bangalore, India, pages 337-344, December 2007. Best paper finalist.

POEM

  1. Meliciani I, Klenin K, Strunk T, Schmitz K, Wenzel W. (2009) Probing hot spots on protein-protein interfaces with all-atom free-energy simulation. J Chem Phys. 131, 034114.

GPUGRID.net

All publications with pdfs are available at http://multiscalelab.org/Publications

  1. T. Giorgino and G. De Fabritiis, A high-throughput steered molecular dynamics study on the free energy profile of ion permeation through gramicidin A, in press J. Chem. Theory Comput. (2011).
  2. I. Buch, S. K. Sadiq and G. De Fabritiis, Optimized potential of mean force calculations of standard binding free energy, in press J. Chem. Theory Comput. (2011)
  3. Ignasi Buch, Toni Giorgino, and G. De Fabritiis, Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations, PNAS 2011 ; published ahead of print June 6, 2011, doi:10.1073/pnas.1103547108
  4. I. Buch, M. J. Harvey, T. Giorgino, D. P. Anderson, and G. De Fabritiis. High-Throughput All-Atom Molecular Dynamics Simulations Using Distributed Computing. J. Chem. Inf. Model, March 2010.
  5. J. Selent, F. Sanz, M. Pastor and G. De Fabritiis, Induced Effects of Sodium Ions on Dopaminergic G-Protein Coupled Receptors, PLOS Computational Biology, 6, e1000884 (2010) pdf.
  6. K. Sadiq and G. De Fabritiis,Explicit solvent dynamics and energetics of HIV-1 protease flap-opening and closing, Proteins 78, 2873 (2010) pdf.
  7. G. Giupponi, M. Harvey and G. De Fabritiis, The impact of accelerator processors for high-throughput molecular modeling and simulation. Drug Discovery Today 13, 1052-8 (2008).
  8. G. De Fabritiis, P. Coveney and J. Villa-Freixa, Energetics of K+ permeability through Gramicidin A by forward-reverse steered molecular dynamics. Proteins 73, 185-94 (2008).
  9. M. Harvey, G. Giupponi, J. Villa-Freixa and G. De Fabritiis, PS3GRID.NET: Building a distributed supercomputer using the PlayStation 3. Distributed & Grid Computing - Science Made Transparent for Everyone. Principles, Applications and Supporting Communities (2007).
  10. PS3GRID.NET: A distributed computing environment for molecular simulations on the PlayStation 3. Presentation at the international symposium of biomedical informatics, 26-27 June Barcelona (2007).
  11. G. De Fabritiis, Performance of the Cell processor for biomolecular simulations. Comp. Phys. Commun. 176, 660 (2007).

QMC@Home

  1. Korth, M., Lüchow, A., and Grimme, S. Toward the Exact Solution of the Electronic Schrödinger Equation for Noncovalent Molecular Interactions: Worldwide Distributed Quantum Monte Carlo Calculations, J. Phys. Chem. A, 112 (10), 2104 -2109.

Quake Catcher Network

  1. Elizabeth S. Cochran, Jesse F. Lawrence, Carl Christensen, and Ravi S. Jakka. The Quake-Catcher Network: Citizen Science Expanding Seismic Horizons. Seismological Research Letters, Jan/Feb 2009.

Rosetta@home

  1. Windbichler N, Menichelli M, Papathanos PA, Thyme SB, Li H, Ulge UY, Hovde BT, Baker D, Monnat RJ Jr, Burt A, Crisanti A. A synthetic homing endonuclease-based gene drive system in the human malaria mosquito. Nature 12;473(7346):212-5 (2011).
  2. Fleishman SJ, Whitehead TA, Ekiert DC, Dreyfus C, Corn JE, Strauch EM, Wilson IA, Baker D. Computational design of proteins targeting the conserved stem region of influenza hemagglutinin. Science 13;332(6031):816-21 (2011).
  3. Karanicolas J, Corn JE, Chen I, Joachimiak LA, Dym O, Peck SH, Albeck S, Unger T, Hu W, Liu G, Delbecq S, T Montelione G, P Spiegel C, Liu DR, Baker D. A de novo protein binding pair by computational design and directed evolution. Mol Cell 42(2):250-60 (2011).
  4. Siegel JB, Zanghellini A, Lovick HM, Kiss G, Lambert AR, St Clair JL, Gallaher JL, Hilvert D, Gelb MH, Stoddard BL, Houk KN, Michael FE, Baker D. Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction. Science 329(5989):309-13 (2010).
  5. Weerapana E, Wang C, Simon GM, Richter F, Khare S, Dillon MB, Bachovchin DA, Mowen K, Baker D, Cravatt BF. Quantitative reactivity profiling predicts functional cysteines in proteomes. Nature 468(7325):790-5 (2010).
  6. Srivatsan Raman, Oliver F. Lange, Paolo Rossi, Michael Tyka, Xu Wang, James Aramini, Gaohua Liu, Theresa A. Ramelot, Alexander Eletsky, Thomas Szyperski, Michael A. Kennedy, James Prestegard, Gaetano T. Montelione, David Baker. NMR Structure Determination for Larger Proteins Using Backbone-Only Data. Science 327, 1014-18 (2010).
  7. Shen Y, Vernon R, Baker D, Bax A. De novo protein structure generation from incomplete chemical shift assignments. J. Biomol. NMR 43, 63-78 (2009).
  8. Das R, Baker D. Prospects for de novo phasing with de novo protein models. Acta Crystallogr. D Biol. Crystallogr. 65, 169-75 (2009).
  9. Das R, André I, Shen Y, Wu Y, Lemak A, Bansal S, Arrowsmith CH, Szyperski T, Baker D. Simultaneous prediction of protein folding and docking at high resolution. Proc. Natl. Acad. Sci. U.S.A. 106, 18978–83 (2009).
  10. Kidd BA, Baker D, Thomas WE. Computation of conformational coupling in allosteric proteins. PLoS Comput. Biol. 5, e1000484 (2009).
  11. Shen Y, Lange O, Delaglio F, Rossi P, Aramini JM, Liu G, Eletsky A, Wu Y, Singarapu KK, Lemak A, Ignatchenko A, Arrowsmith CH, Szyperski T, Montelione GT, Baker D, Bax A. Consistent blind protein structure generation from NMR chemical shift data. Proc. Natl. Acad. Sci. U.S.A. 105, 4685-90 (2008).
  12. Rhiju Das, Madhuri Kudaravalli, Magdalena Jonikas, Alain Laederach, Robert Fong, Jason P. Schwans, David Baker, Joseph A. Piccirilli, Russ B. Altman, and Daniel Herschlag. Structural inference of native and partially folded RNA by high throughput contact mapping. Proc. Natl. Acad. Sci. U.S.A. 105, 4144-9 (2008).
  13. Qian B, Raman S, Das R, Bradley P, McCoy AJ, Read RJ, Baker D. High-resolution structure prediction and the crystallographic phase problem. Nature 450, 259-64 (2007).
  14. Wang C, Bradley P, Baker D. Protein-protein docking with backbone flexibility. J. Mol. Biol. 373, 503-19 (2007).
  15. Das R, Qian B, Raman S, Vernon R, Thompson J, Bradley P, Khare S, Tyka MD, Bhat D, Chivian D, Kim DE, Sheffler WH, Malmström L, Wollacott AM, Wang C, Andre I, Baker D. Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home. Proteins 69 Suppl 8, 118-28 (2007).
  16. Das R, Baker D. Automated de novo prediction of native-like RNA tertiary structures. Proc. Natl. Acad. Sci. U.S.A. 104, 14664-9 (2007).
  17. Misura KM, Chivian D, Rohl CA, Kim DE, Baker D. Physically realistic homology models built with ROSETTA can be more accurate than their templates. Proc. Natl. Acad. Sci. U.S.A. 103, 5361-6 (2006).

SETI@home

  1. David P. Anderson, Jeff Cobb, Eric Korpela, Matt Lebofsky, Dan Werthimer. SETI@home: An Experiment in Public-Resource Computing. Communications of the ACM, Vol. 45 No. 11, November 2002, pp. 56-61.

SIMAP

  1. Rattei T, Tischler P, Arnold R, Hamberger F, Krebs J, Krumsiek J, Wachinger B, Stümpflen V, Mewes W. SIMAP--structuring the network of protein similarities. Nucleic Acids Res. 2008 Jan;36(Database issue):D289-92. Epub 2007 Nov 23.
  2. Rattei T, Arnold R, Tischler P, Lindner D, Stümpflen V, Mewes HW. SIMAP: the similarity matrix of proteins. Nucleic Acids Res. 2006 Jan 1;34(Database issue):D252-6.
  3. Arnold R, Rattei T, Tischler P, Truong MD, Stümpflen V, Mewes W. SIMAP--the similarity matrix of proteins. Bioinformatics. 2005 Sep 1;21 Suppl 2:ii42-6.

Spinhenge@home

  1. Christian Schröder, Ruslan Prozorov, Paul Kögerler, Matthew D. Vannette, Xikui Fang, Marshall Luban, Akira Matsuo, Koichi Kindo, Achim Müller, Ana Maria Todea, Multiple nearest-neighbor exchange model for the frustrated Keplerate magnetic molecules Mo72Fe30 and Mo72Cr30. submitted to Phys. Rev. B (2008), arXiv.org e-Print archiv, Jan 2008

uFluids

  1. Robert E Manning & Steven H. Collicott, Bubble Penetration Through a Single Layer Sphere Bed. 45th AIAA Aerospace Sciences Meeting and Exhibit, January 2006.
  2. Robert E. Manning Jr, Gas Bubble Stability in a Sphere Layer, Master Thesis - July 2006.
  3. Jonathan P. Braun, Zero Gravity Two-Phase Stability Solutions of Droplets in a bent circular cylinder, Master Thesis - 2008.

Virtual Prairie

  1. C. Monya, M. Garbeyb, M. Smaouib, M.-L. Benota. Large scale parameter study of an individual-based model of clonal plant with volunteer computing. Ecological Modelling 222 (2011) 935–946.

World Community Grid

Help Cure Muscular Dystrophy

  1. Sophie Sacquin-Mora1, Alessandra Carbone, and Richard Lavery. Identification of Protein Interaction Partners and Protein–Protein Interaction Sites Journal of Molecular Biology, 2008 Aug 7.
  2. V. Bertsis, R. Bolze, F. Desprez, K. Reed. Large Scale Execution of a Bioinformatic Application on a Volunteer Grid. Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC), In conjunction with IPDPS 2008, Miami, Florida, April, 2008.
  3. Viktors Bertis, Raphaël Bolze, Frédéric Desprez and Kevin Reed. [http://www.springerlink.com/content/d285t3w3m4126l01/ From Dedicated Grid to Volunteer Grid: Large Scale Execution of a Bioinformatics Application

FightAIDS@Home

  1. Max W. Chang, William Lindstrom, Arthur J. Olson, and Richard K. Belew . Analysis of HIV Wild-Type and Mutant Structures via in Silico Docking against Diverse Ligand Libraries. J. Chem. Inf. Model., 47 (3), 1258 -1262, 2007.

Human Proteome Folding - Phase I

  1. Lars Malmström, Michael Riffle, Charlie E. M. Strauss, Dylan Chivian, Trisha N. Davis, Richard Bonneau, David Baker. Superfamily Assignments for the Yeast Proteome through Integration of Structure Prediction with the Gene Ontology. PLoS Biol 5(4).

Help Defeat Cancer

  1. Lin Yang, Wenjin Chen, Peter Meer1, Gratian Salaru, Michael D. Feldman, and David J. Foran High Throughput Analysis of Breast Cancer Specimens on the Grid. Proceedings on Medical Image Computing and Computer-Assisted Intervention. (MICCAI) Brisbane, Australia. October, 2007.

Help Conquer Cancer

  1. C.A. Cumbaa & I. Jurisica, Scale Changes Everything – Crystallography Image Analysis on the World Community Grid. 22nd High Performance Computing Symposium - Québec City, CA. June, 2008

Computing for Clean Water

  1. Ming D. Ma, Luming Shen,*, John Sheridan, Jefferson Zhe Liu, Chao Chen, and Quanshui Zheng Friction of water slipping in carbon nanotubes.

Nutritious Rice for the World

  1. Ling-Hong Hung, Michal Guerquin and Ram Samudrala GPU-Q-J, a fast method for calculating root mean square deviation (RMSD) after optimal superposition.

Yoyo@home

Evolution@home

  1. Laurence Loewe, Asher D Cutter, On the potential for extinction by Muller's Ratchet in Caenorhabditis elegans, BMC Evolutionary Biology 8:125.
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