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An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12.
Scientific Reports (2018)
  • Chen Keasar, Ben-Gurion University of the Negev
  • Liam J. McGuffin, University of Reading
  • Björn Wallner, Linköping University
  • Gaurav Chopra
  • Badri Adhikari, University of Missouri
  • Debswapna Bhattacharya, Auburn University
  • Lauren Blake, Lawrence Berkeley National Laboratory
  • Leandro Oliveira Bortot, University of São Paulo
  • Renzhi Cao, University of Missouri
  • B. K. Dhanasekaran, Indian Institute of Science
  • Itzhel Dimas, Lawrence Berkeley National Laboratory
  • Rodrigo Antonio Faccioli, University of São Paulo
  • Eshel Faraggi, The Research Institute at Nationwide Children's Hospital
  • Robert Ganzynkowicz, University of Gdańsk
  • Sambit Ghosh, Indian Institute of Science
  • Soma Ghosh, Indian Institute of Science
  • Artur Giełdoń, University of Gdańsk
  • Lukasz Golon, University of Gdańsk
  • Yi He, University of California, Merced
  • Lim Heo, Seoul National University
  • Jie Hou, University of Missouri
  • Main Khan, University of Massachusetts Dartmouth
  • Firas Khatib, University of Massachusetts Dartmouth
  • George A. Khoury, Princeton University
  • Chris Kieslich, Texas A&M University
  • David E. Kim, University of Washington
  • Pawel Krupa, University of Gdańsk
  • Gyu Rie Lee, Seoul National University
  • Hongbo Li, Northeast Normal University
  • Jilong Li, University of Missouri
  • Agnieszka Lipska, University of Gdańsk
  • Adam Liwo, University of Gdańsk
  • Ali Hassan A. Maghrabi, University of Reading
  • Milot Mirdita, Max Planck Society
  • Shokoufeh Mirzaei, California State Polytechnic University, Pomona
  • Magdalena A. Mozolewska, University of Gdańsk
  • Melis Onel, Texas A&M University
  • Sergey Ovchinnikov, University of Washington
  • Anand Shah, University of Massachusetts Dartmouth
  • Utkarsh Shah, Texas A&M University
  • Tomer Sidi, Ben-Gurion University of the Negev
  • Adam K. Sieradzan, University of Gdańsk
  • Magdalena Ślusarz, University of Gdańsk
  • Rafal Ślusarz, University of Gdańsk
  • James Smadbeck, Princeton University
  • Phanourios Tamamis, Texas A&M University
  • Nicholas Trieber, University of Massachusetts Dartmouth
  • Tomasz Wirecki, University of Gdańsk
  • Yanping Yin, Cornell University
Abstract
Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has signifcantly advanced the feld but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based efort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other felds to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this efort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.
Publication Date
December 1, 2018
DOI
10.1038/s41598-018-26812-8
Publisher Statement
Published by 'BMC Bioinformatics' at 10.1186/s12859-015-0775-x.
Citation Information
Chen Keasar, Liam J. McGuffin, Björn Wallner, Gaurav Chopra, et al.. "An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12." Scientific Reports Vol. 8 Iss. 1 (2018) p. 9939
Available at: http://works.bepress.com/badri-adhikari/12/
Creative Commons license
Creative Commons License
This work is licensed under a Creative Commons CC_BY International License.