Vickie Curtis: Patterns of Participation and Motivation in Folding@home: The Contribution of Hardware Enthusiasts and Overclockers. In: Citizen Science: Theory and Practice. Band3, Nr.1, 27. April 2018, ISSN2057-4991, S.5, doi:10.5334/cstp.109 (citizenscienceassociation.org [abgerufen am 20. März 2020]).
Vijay S. Pande, Kyle Beauchamp, Gregory R. Bowman: Everything you wanted to know about Markov State Models but were afraid to ask. In: Methods (San Diego CA). Band52, Nr.1, September 2010, ISSN1046-2023, S.99–105, doi:10.1016/j.ymeth.2010.06.002, PMID 20570730, PMC 2933958 (freier Volltext).
Matthew P. Harrigan, Mohammad M. Sultan, Carlos X. Hernández, Brooke E. Husic, Peter Eastman: MSMBuilder: Statistical Models for Biomolecular Dynamics. In: Biophysical Journal. Band112, Nr.1, 10. Januar 2017, ISSN1542-0086, S.10–15, doi:10.1016/j.bpj.2016.10.042, PMID 28076801, PMC 5232355 (freier Volltext).
G. Zhang, Z. Ignatova: Folding at the birth of the nascent chain: coordinating translation with co-translational folding. In: Current opinion in structural biology. Band 21, Nummer 1, Februar 2011, S. 25–31, doi:10.1016/j.sbi.2010.10.008, PMID 21111607 (Review).
B. van den Berg, R. Wain, C. M. Dobson, R. J. Ellis: Macromolecular crowding perturbs protein refolding kinetics: implications for folding inside the cell. In: The EMBO Journal. Band 19, Nummer 15, August 2000, S. 3870–3875, doi:10.1093/emboj/19.15.3870, PMID 10921869, PMC 306593 (freier Volltext).
F. Marinelli, F. Pietrucci, A. Laio, S. Piana: A kinetic model of trp-cage folding from multiple biased molecular dynamics simulations. In: PLoS Computational Biology. Band 5, Nummer 8, August 2009, S. e1000452, doi:10.1371/journal.pcbi.1000452, PMID 19662155, PMC 2711228 (freier Volltext).
H. Ecroyd, J. A. Carver: Unraveling the mysteries of protein folding and misfolding. In: IUBMB life. Band 60, Nummer 12, Dezember 2008, S. 769–774, doi:10.1002/iub.117, PMID 18767168 (Review).
Y. Chen, F. Ding, H. Nie, A. W. Serohijos, S. Sharma, K. C. Wilcox, S. Yin, N. V. Dokholyan: Protein folding: then and now. In: Archives of biochemistry and biophysics. Band 469, Nummer 1, Januar 2008, S. 4–19, doi:10.1016/j.abb.2007.05.014, PMID 17585870, PMC 2173875 (freier Volltext).
L. M. Luheshi, D. C. Crowther, C. M. Dobson: Protein misfolding and disease: from the test tube to the organism. In: Current opinion in chemical biology. Band 12, Nummer 1, Februar 2008, S. 25–31, doi:10.1016/j.cbpa.2008.02.011, PMID 18295611 (Review).
C. D. Snow, E. J. Sorin, Y. M. Rhee, V. S. Pande: How well can simulation predict protein folding kinetics and thermodynamics? In: Annual review of biophysics and biomolecular structure. Band 34, 2005, S. 43–69, doi:10.1146/annurev.biophys.34.040204.144447, PMID 15869383 (Review).
V. S. Pande, I. Baker, J. Chapman, S. P. Elmer, S. Khaliq, S. M. Larson, Y. M. Rhee, M. R. Shirts, C. D. Snow, E. J. Sorin, B. Zagrovic: Atomistic protein folding simulations on the submillisecond time scale using worldwide distributed computing. In: Biopolymers. Band 68, Nummer 1, Januar 2003, S. 91–109, doi:10.1002/bip.10219, PMID 12579582.
G. R. Bowman, V. A. Voelz, V. S. Pande: Taming the complexity of protein folding. In: Current opinion in structural biology. Band 21, Nummer 1, Februar 2011, S. 4–11, doi:10.1016/j.sbi.2010.10.006, PMID 21081274, PMC 3042729 (freier Volltext) (Review).
John D. Chodera, William C. Swope, Jed W. Pitera, Ken A. Dill: Long-Time Protein Folding Dynamics from Short-Time Molecular Dynamics Simulations. In: Multiscale Modeling & Simulation. Band 5, 2006, S. 1214, doi:10.1137/06065146X.
R. B. Best: Atomistic molecular simulations of protein folding. In: Current opinion in structural biology. Band 22, Nummer 1, Februar 2012, S. 52–61, doi:10.1016/j.sbi.2011.12.001, PMID 22257762 (Review).
V. S. Pande, K. Beauchamp, G. R. Bowman: Everything you wanted to know about Markov State Models but were afraid to ask. In: Methods. Band 52, Nummer 1, September 2010, S. 99–105, doi:10.1016/j.ymeth.2010.06.002, PMID 20570730, PMC 2933958 (freier Volltext) (Review).
G. R. Bowman, D. L. Ensign, V. S. Pande: Enhanced modeling via network theory: Adaptive sampling of Markov state models. In: Journal of chemical theory and computation. Band 6, Nummer 3, 2010, S. 787–794, doi:10.1021/ct900620b, PMID 23626502, PMC 3637129 (freier Volltext).
Brooke E. Husic, Vijay S. Pande: Markov State Models: From an Art to a Science. In: Journal of the American Chemical Society. Band140, Nr.7, 21. Februar 2018, ISSN1520-5126, S.2386–2396, doi:10.1021/jacs.7b12191, PMID 29323881.
C. D. Snow, H. Nguyen, V. S. Pande, M. Gruebele: Absolute comparison of simulated and experimental protein-folding dynamics. In: Nature. Band 420, Nummer 6911, November 2002, S. 102–106, doi:10.1038/nature01160, PMID 12422224.
Pande Lab Science [Stanford University]: Simulation of millisecond protein folding: NTL9 (from Folding@home) auf YouTube, 18. Januar 2010, abgerufen am 23. März 2020 (englisch. Simulating protein folding on the millisecond timescale has been a major challenge for many years. In a recent paper (doi:10.1021/ja9090353), Folding@home researchers Vincent Voelz, Greg Bowman, Kyle Beauchamp, and Vijay Pande have broken this barrier. This is a movie of one of the trajectories that folded (i.e. started unfolded and ended up in the folded state)).
Hana Robson Marsden, Itsuro Tomatsu, Alexander Kros: Model systems for membrane fusion. In: Chemical Society Reviews. Band40, Nr.3, 22. Februar 2011, ISSN1460-4744, S.1572–1585, doi:10.1039/C0CS00115E.
Gregory R Bowman, Xuhui Huang, Vijay S Pande: Network models for molecular kinetics and their initial applications to human health. In: Cell research. Band20, Nr.6, Juni 2010, ISSN1001-0602, S.622–630, doi:10.1038/cr.2010.57, PMID 20421891, PMC 4441225 (freier Volltext).
Peter M. Kasson, Afra Zomorodian, Sanghyun Park, Nina Singhal, Leonidas J. Guibas: Persistent voids: a new structural metric for membrane fusion. In: Bioinformatics. Band23, Nr.14, 15. Juli 2007, ISSN1367-4803, S.1753–1759, doi:10.1093/bioinformatics/btm250 (academic.oup.com [abgerufen am 18. März 2020]).
Peter M. Kasson, Daniel L. Ensign, Vijay S. Pande: Combining molecular dynamics with Bayesian analysis to predict and evaluate ligand-binding mutations in influenza hemagglutinin. In: Journal of the American Chemical Society. Band131, Nr.32, 19. August 2009, ISSN0002-7863, S.11338–11340, doi:10.1021/ja904557w, PMID 19637916, PMC 2737089 (freier Volltext).
Christian Gruber, Georg Steinkellner: Wuhan coronavirus 2019-nCoV – what we can find out on a structural bioinformatics level. In: Innophore. 29. Januar 2020, doi:10.6084/m9.figshare.11752749 (englisch).
J. Rajadas, C. W. Liu, P. Novick, N. W. Kelley, M. Inayathullah, M. C. Lemieux, V. S. Pande: Rationally designed turn promoting mutation in the amyloid-β peptide sequence stabilizes oligomers in solution. In: PLOS ONE. Band 6, Nummer 7, 2011, S. e21776, doi:10.1371/journal.pone.0021776, PMID 21799748, PMC 3142112 (freier Volltext).
Nicholas W. Kelley; Xuhui Huang; Stephen Tam; Christoph Spiess; Judith Frydman; Vijay S. Pande: The predicted structure of the headpiece of the Huntingtin protein and its implications on Huntingtin aggregation. In: Journal of Molecular Biology, 2009, 388 (5), S. 919–927. doi:10.1016/j.jmb.2009.01.032
M. S. Friedrichs, P. Eastman, V. Vaidyanathan, M. Houston, S. Legrand, A. L. Beberg, D. L. Ensign, C. M. Bruns, V. S. Pande: Accelerating molecular dynamic simulation on graphics processing units. In: Journal of computational chemistry. Band 30, Nummer 6, April 2009, S. 864–872, doi:10.1002/jcc.21209, PMID 19191337, PMC 2724265 (freier Volltext).
E. Luttmann, D. L. Ensign, V. Vaidyanathan, M. Houston, N. Rimon, J. Øland, G. Jayachandran, M. Friedrichs, V. S. Pande: Accelerating molecular dynamic simulation on the cell processor and Playstation 3. In: Journal of computational chemistry. Band 30, Nummer 2, Januar 2009, S. 268–274, doi:10.1002/jcc.21054, PMID 18615421.
Vickie Curtis: Patterns of Participation and Motivation in Folding@home: The Contribution of Hardware Enthusiasts and Overclockers. In: Citizen Science: Theory and Practice. Band3, Nr.1, 27. April 2018, ISSN2057-4991, S.5, doi:10.5334/cstp.109 (citizenscienceassociation.org [abgerufen am 20. März 2020]).
Marc F. Lensink, Raúl Méndez, Shoshana J. Wodak: Docking and scoring protein complexes: CAPRI 3rd Edition. In: Proteins: Structure, Function, and Bioinformatics. Band69, Nr.4, 2007, ISSN1097-0134, S.704–718, doi:10.1002/prot.21804.
Public Launch. Stanford University, 19. September 2000, abgerufen am 22. März 2020 (englisch): „We released our software to the public and very soon after we had thousands of computers donating otherwise unused computer power.“
Folding@Home FAQ. In: foldingathome.org. Abgerufen am 6. März 2020 (englisch).
What are native FLOPS? In: FAQs. Folding@Home, abgerufen am 23. März 2020 (englisch): „We refer to the FLOP count on a given hardware as the native FLOP count. For example, an exponential on a GPU is one native GPU FLOP but many native x86-FLOPS.“
Running Folding@Home. In: foldingathome.org. Abgerufen am 23. März 2020 (englisch): „These unfinished work units ‘expire’ and are reassigned to new machines. You will still receive credit for all WUs completed and uploaded prior to the Timeout (formerly preferred deadline).“
Requirements. In: foldingathome.org. Abgerufen am 23. März 2020 (englisch): „CPU Slot Requirements Windows XP SP3 or newer, 32 or 64 bit Intel P4 1.4 GHz processor or newer, or AMD equivalent (modern multi-core processors recommended)“
Anto Thynell: android-client-overhaul. 2. Februar 2018, abgerufen am 6. März 2020 (englisch): „From the 16th of February 2018, it will no longer be possible to use the Folding@Home Android client from Sony“
Vijay Pande: Changes to F@h Website. In: foldingforum.org. 25. Oktober 2011, abgerufen am 23. März 2020 (englisch). “We have been making these available in general on request and in cases where people ask for data sets repeatedly (eg simtk.org we make them available on a website linked from folding.stanford.edu.”
Greg Bowman: Folding Forum • Login. 22. August 2011, abgerufen am 18. März 2020 (englisch): „This A3 project for windows and linux clients aims to characterize the dynamics of RNase H, a key component of HIV. By understanding the role of dynamics in its mechanism, we hope to be better able to design drugs to deactivate this enzyme.“
Kiona Smith: SETI@Home Is Over; The Fight Against COVID-19 Coronavirus Is Just Beginning. Forbes Magazine, 15. März 2020, abgerufen am 22. März 2020 (englisch): „Folding@Home (a program similar to SETI@Home that focuses on disease research – specifically how proteins fold) just rolled out “an initial wave of projects” that simulate how proteins from SARS-CoV-2 (the virus that causes COVID-19) work and how they interact with human cells.“
Folding@home 3D Viewer. Github, abgerufen am 23. März 2020 (englisch): „The Folding@home viewer allows you to visualize protein folding simulations and monitor the status of the simulation work units as they run on your computer. Installing and running the viewer is not necessary to run Folding@home.“
Most powerful distributed computing network. Guinness World Records Limited, 16. September 2007, abgerufen am 22. März 2020 (englisch): „On 16 September 2007 Folding@home, a distributed computing network operating from Stanford University (USA) achieved a computing power of 1 petaflop – or 1 quadrillion floating point operations per second.“
hicomb.org
Adam Beberg, Daniel Ensign, Guha Jayachandran, Siraj Khaliq, Vijay Pande: Folding@home: Lessons from eight years of volunteer distributed computing. (PDF; 304 kB) In: hicomb.org. 2009 IEEE International Symposium on Parallel & Distributed Processing. Proceedings, 2009, abgerufen am 18. März 2020.
Guest Recorder: 3 PetaFLOP barrier – PetScience. LongeCity – Advocacy & Research for Unlimited Lifespans, 19. August 2008, abgerufen am 6. März 2020 (englisch).
Susan W Liebman: Protein folding: Sticky N17 speeds huntingtin pile-up. Springer Nature Limited, Januar 2010, abgerufen am 23. März 2020 (englisch): „Aggregation of huntingtin protein with an expanded polyglutamine region is enhanced by its 17-residue N-terminal domain, which binds to itself and to the polyglutamine region. This enhancement is inhibited when the N-terminal domain binds to the chaperonin TRiC.“
nih.gov
ncbi.nlm.nih.gov
Vijay S. Pande, Kyle Beauchamp, Gregory R. Bowman: Everything you wanted to know about Markov State Models but were afraid to ask. In: Methods (San Diego CA). Band52, Nr.1, September 2010, ISSN1046-2023, S.99–105, doi:10.1016/j.ymeth.2010.06.002, PMID 20570730, PMC 2933958 (freier Volltext).
Matthew P. Harrigan, Mohammad M. Sultan, Carlos X. Hernández, Brooke E. Husic, Peter Eastman: MSMBuilder: Statistical Models for Biomolecular Dynamics. In: Biophysical Journal. Band112, Nr.1, 10. Januar 2017, ISSN1542-0086, S.10–15, doi:10.1016/j.bpj.2016.10.042, PMID 28076801, PMC 5232355 (freier Volltext).
G. Zhang, Z. Ignatova: Folding at the birth of the nascent chain: coordinating translation with co-translational folding. In: Current opinion in structural biology. Band 21, Nummer 1, Februar 2011, S. 25–31, doi:10.1016/j.sbi.2010.10.008, PMID 21111607 (Review).
B. van den Berg, R. Wain, C. M. Dobson, R. J. Ellis: Macromolecular crowding perturbs protein refolding kinetics: implications for folding inside the cell. In: The EMBO Journal. Band 19, Nummer 15, August 2000, S. 3870–3875, doi:10.1093/emboj/19.15.3870, PMID 10921869, PMC 306593 (freier Volltext).
F. Marinelli, F. Pietrucci, A. Laio, S. Piana: A kinetic model of trp-cage folding from multiple biased molecular dynamics simulations. In: PLoS Computational Biology. Band 5, Nummer 8, August 2009, S. e1000452, doi:10.1371/journal.pcbi.1000452, PMID 19662155, PMC 2711228 (freier Volltext).
H. Ecroyd, J. A. Carver: Unraveling the mysteries of protein folding and misfolding. In: IUBMB life. Band 60, Nummer 12, Dezember 2008, S. 769–774, doi:10.1002/iub.117, PMID 18767168 (Review).
Y. Chen, F. Ding, H. Nie, A. W. Serohijos, S. Sharma, K. C. Wilcox, S. Yin, N. V. Dokholyan: Protein folding: then and now. In: Archives of biochemistry and biophysics. Band 469, Nummer 1, Januar 2008, S. 4–19, doi:10.1016/j.abb.2007.05.014, PMID 17585870, PMC 2173875 (freier Volltext).
L. M. Luheshi, D. C. Crowther, C. M. Dobson: Protein misfolding and disease: from the test tube to the organism. In: Current opinion in chemical biology. Band 12, Nummer 1, Februar 2008, S. 25–31, doi:10.1016/j.cbpa.2008.02.011, PMID 18295611 (Review).
C. D. Snow, E. J. Sorin, Y. M. Rhee, V. S. Pande: How well can simulation predict protein folding kinetics and thermodynamics? In: Annual review of biophysics and biomolecular structure. Band 34, 2005, S. 43–69, doi:10.1146/annurev.biophys.34.040204.144447, PMID 15869383 (Review).
V. S. Pande, I. Baker, J. Chapman, S. P. Elmer, S. Khaliq, S. M. Larson, Y. M. Rhee, M. R. Shirts, C. D. Snow, E. J. Sorin, B. Zagrovic: Atomistic protein folding simulations on the submillisecond time scale using worldwide distributed computing. In: Biopolymers. Band 68, Nummer 1, Januar 2003, S. 91–109, doi:10.1002/bip.10219, PMID 12579582.
G. R. Bowman, V. A. Voelz, V. S. Pande: Taming the complexity of protein folding. In: Current opinion in structural biology. Band 21, Nummer 1, Februar 2011, S. 4–11, doi:10.1016/j.sbi.2010.10.006, PMID 21081274, PMC 3042729 (freier Volltext) (Review).
R. B. Best: Atomistic molecular simulations of protein folding. In: Current opinion in structural biology. Band 22, Nummer 1, Februar 2012, S. 52–61, doi:10.1016/j.sbi.2011.12.001, PMID 22257762 (Review).
V. S. Pande, K. Beauchamp, G. R. Bowman: Everything you wanted to know about Markov State Models but were afraid to ask. In: Methods. Band 52, Nummer 1, September 2010, S. 99–105, doi:10.1016/j.ymeth.2010.06.002, PMID 20570730, PMC 2933958 (freier Volltext) (Review).
G. R. Bowman, D. L. Ensign, V. S. Pande: Enhanced modeling via network theory: Adaptive sampling of Markov state models. In: Journal of chemical theory and computation. Band 6, Nummer 3, 2010, S. 787–794, doi:10.1021/ct900620b, PMID 23626502, PMC 3637129 (freier Volltext).
Brooke E. Husic, Vijay S. Pande: Markov State Models: From an Art to a Science. In: Journal of the American Chemical Society. Band140, Nr.7, 21. Februar 2018, ISSN1520-5126, S.2386–2396, doi:10.1021/jacs.7b12191, PMID 29323881.
C. D. Snow, H. Nguyen, V. S. Pande, M. Gruebele: Absolute comparison of simulated and experimental protein-folding dynamics. In: Nature. Band 420, Nummer 6911, November 2002, S. 102–106, doi:10.1038/nature01160, PMID 12422224.
Gregory R Bowman, Xuhui Huang, Vijay S Pande: Network models for molecular kinetics and their initial applications to human health. In: Cell research. Band20, Nr.6, Juni 2010, ISSN1001-0602, S.622–630, doi:10.1038/cr.2010.57, PMID 20421891, PMC 4441225 (freier Volltext).
Peter M. Kasson, Daniel L. Ensign, Vijay S. Pande: Combining molecular dynamics with Bayesian analysis to predict and evaluate ligand-binding mutations in influenza hemagglutinin. In: Journal of the American Chemical Society. Band131, Nr.32, 19. August 2009, ISSN0002-7863, S.11338–11340, doi:10.1021/ja904557w, PMID 19637916, PMC 2737089 (freier Volltext).
J. Rajadas, C. W. Liu, P. Novick, N. W. Kelley, M. Inayathullah, M. C. Lemieux, V. S. Pande: Rationally designed turn promoting mutation in the amyloid-β peptide sequence stabilizes oligomers in solution. In: PLOS ONE. Band 6, Nummer 7, 2011, S. e21776, doi:10.1371/journal.pone.0021776, PMID 21799748, PMC 3142112 (freier Volltext).
M. S. Friedrichs, P. Eastman, V. Vaidyanathan, M. Houston, S. Legrand, A. L. Beberg, D. L. Ensign, C. M. Bruns, V. S. Pande: Accelerating molecular dynamic simulation on graphics processing units. In: Journal of computational chemistry. Band 30, Nummer 6, April 2009, S. 864–872, doi:10.1002/jcc.21209, PMID 19191337, PMC 2724265 (freier Volltext).
E. Luttmann, D. L. Ensign, V. Vaidyanathan, M. Houston, N. Rimon, J. Øland, G. Jayachandran, M. Friedrichs, V. S. Pande: Accelerating molecular dynamic simulation on the cell processor and Playstation 3. In: Journal of computational chemistry. Band 30, Nummer 2, Januar 2009, S. 268–274, doi:10.1002/jcc.21054, PMID 18615421.
oup.com
academic.oup.com
Peter M. Kasson, Afra Zomorodian, Sanghyun Park, Nina Singhal, Leonidas J. Guibas: Persistent voids: a new structural metric for membrane fusion. In: Bioinformatics. Band23, Nr.14, 15. Juli 2007, ISSN1367-4803, S.1753–1759, doi:10.1093/bioinformatics/btm250 (academic.oup.com [abgerufen am 18. März 2020]).
Pande lab: Opensource. In: webcitation.org. 3. August 2012, archiviert vom Original (nicht mehr online verfügbar) am 3. März 2020; abgerufen am 18. März 2020.
Windows V7 Client. Stanford University, 18. August 2012, ehemals im Original (nicht mehr online verfügbar); abgerufen am 6. März 2020 (englisch): „We are pleased to say that everything is new in this version, using completely new software coding from the ground up.“
Folding@home Chrome Client. Archiviert vom Original (nicht mehr online verfügbar) am 12. April 2019; abgerufen am 6. März 2020 (englisch): „Our decision to retire the NaCl client was due to a combination of Google deprecating NaCl and infrastructure upgrades at Folding@home which would have required extra effort to continue to support the NaCl folding client.“
Vijay Grande: Folding@home vs. Rosetta@home. 5. März 2006, archiviert vom Original (nicht mehr online verfügbar) am 19. Mai 2020; abgerufen am 19. März 2020 (englisch): „However, Rosetta and Folding@Home are addressing very different problems.
Rosetta only predicts the final folded state, not how do proteins fold (and Rosetta has nothing to do with protein misfolding). Thus, those methods are not useful for the questions we’re interested in and the diseases we’re tackling (Alzheimer’s Disease and other aggregation related diseases).“
Vijay Pande: Changes to F@h Website. In: foldingforum.org. 25. Oktober 2011, abgerufen am 23. März 2020 (englisch). “We have been making these available in general on request and in cases where people ask for data sets repeatedly (eg simtk.org we make them available on a website linked from folding.stanford.edu.”
Vijay Pande: Folding@home and Simbios. In: typepad.com. 23. April 2008, abgerufen am 23. März 2020 (englisch): „Second, we’re also starting to make large data sets from Folding@home available to others. You can see some of the first data sets on this project page, and we expect to put more data up as time goes on. Folding@home donors have generated wonderful data sets that aren’t possible to generate by other means, and our hope is to publish them so that other scientists can data mine them for other purposes as well.“
Gregory Bowman: Searching for new drug targets. Folding@home. foldingathome.org. Archivierung des Originals am 21. September 2012. Abgerufen am 20. März 2020.
Crossing the petaflop barrier. In: Folding@home A blog all about Folding@home, from its Director, Prof. Vijay Pande. 16. September 2007, abgerufen am 6. März 2020 (englisch).
Client version 7 now in open beta. 9. März 2011, abgerufen am 6. März 2020 (englisch): „I am happy to announce that after many months of development and testing the new version 7 Folding@home client software is now available for open-beta testing. The V7 client is a complete rewrite of the previous client for Windows, OS-X and Linux with the following goals.“
Pande lab: Opensource. In: webcitation.org. 3. August 2012, archiviert vom Original (nicht mehr online verfügbar) am 3. März 2020; abgerufen am 18. März 2020.
Folding@home Chrome Client. Archiviert vom Original (nicht mehr online verfügbar) am 12. April 2019; abgerufen am 6. März 2020 (englisch): „Our decision to retire the NaCl client was due to a combination of Google deprecating NaCl and infrastructure upgrades at Folding@home which would have required extra effort to continue to support the NaCl folding client.“
Vijay Grande: Folding@home vs. Rosetta@home. 5. März 2006, archiviert vom Original (nicht mehr online verfügbar) am 19. Mai 2020; abgerufen am 19. März 2020 (englisch): „However, Rosetta and Folding@Home are addressing very different problems.
Rosetta only predicts the final folded state, not how do proteins fold (and Rosetta has nothing to do with protein misfolding). Thus, those methods are not useful for the questions we’re interested in and the diseases we’re tackling (Alzheimer’s Disease and other aggregation related diseases).“
webcitation.org
Award. (Memento vom 21. September 2012 auf WebCite) In: folding.stanford.edu, abgerufen am 18. März 2020.
Julia Evangelou Strait: Bowman leading international supercomputing project. Washington University School of Medicine in St. Louis, 26. Februar 2019, abgerufen am 19. März 2020 (englisch): „With this networked computing power, Folding@home is, essentially, one of the world’s largest supercomputers.“
Pande Lab Science [Stanford University]: Simulation of millisecond protein folding: NTL9 (from Folding@home) auf YouTube, 18. Januar 2010, abgerufen am 23. März 2020 (englisch. Simulating protein folding on the millisecond timescale has been a major challenge for many years. In a recent paper (doi:10.1021/ja9090353), Folding@home researchers Vincent Voelz, Greg Bowman, Kyle Beauchamp, and Vijay Pande have broken this barrier. This is a movie of one of the trajectories that folded (i.e. started unfolded and ended up in the folded state)).
Vijay S. Pande, Kyle Beauchamp, Gregory R. Bowman: Everything you wanted to know about Markov State Models but were afraid to ask. In: Methods (San Diego CA). Band52, Nr.1, September 2010, ISSN1046-2023, S.99–105, doi:10.1016/j.ymeth.2010.06.002, PMID 20570730, PMC 2933958 (freier Volltext).
Matthew P. Harrigan, Mohammad M. Sultan, Carlos X. Hernández, Brooke E. Husic, Peter Eastman: MSMBuilder: Statistical Models for Biomolecular Dynamics. In: Biophysical Journal. Band112, Nr.1, 10. Januar 2017, ISSN1542-0086, S.10–15, doi:10.1016/j.bpj.2016.10.042, PMID 28076801, PMC 5232355 (freier Volltext).
Brooke E. Husic, Vijay S. Pande: Markov State Models: From an Art to a Science. In: Journal of the American Chemical Society. Band140, Nr.7, 21. Februar 2018, ISSN1520-5126, S.2386–2396, doi:10.1021/jacs.7b12191, PMID 29323881.
Hana Robson Marsden, Itsuro Tomatsu, Alexander Kros: Model systems for membrane fusion. In: Chemical Society Reviews. Band40, Nr.3, 22. Februar 2011, ISSN1460-4744, S.1572–1585, doi:10.1039/C0CS00115E.
Gregory R Bowman, Xuhui Huang, Vijay S Pande: Network models for molecular kinetics and their initial applications to human health. In: Cell research. Band20, Nr.6, Juni 2010, ISSN1001-0602, S.622–630, doi:10.1038/cr.2010.57, PMID 20421891, PMC 4441225 (freier Volltext).
Peter M. Kasson, Afra Zomorodian, Sanghyun Park, Nina Singhal, Leonidas J. Guibas: Persistent voids: a new structural metric for membrane fusion. In: Bioinformatics. Band23, Nr.14, 15. Juli 2007, ISSN1367-4803, S.1753–1759, doi:10.1093/bioinformatics/btm250 (academic.oup.com [abgerufen am 18. März 2020]).
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