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Ian R. Humphreys
Researcher at University of Washington
Publications - 5
Citations - 273
Ian R. Humphreys is an academic researcher from University of Washington. The author has contributed to research in topics: Pipeline (computing) & Protein structure prediction. The author has an hindex of 3, co-authored 5 publications receiving 20 citations.
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Journal ArticleDOI
Computed structures of core eukaryotic protein complexes.
Ian R. Humphreys,Jimin Pei,Minkyung Baek,Aditya Krishnakumar,Ivan Anishchenko,Sergey Ovchinnikov,Jing Zhang,Travis J. Ness,Sudeep Banjade,Saket R. Bagde,Viktoriya G. Stancheva,Xiao-Han Li,Kaixian Liu,Zhi Zheng,Zhi Zheng,Daniel J. Barrero,Upasana Roy,Jochen Kuper,Israel S. Fernández,Barnabas Szakal,Dana Branzei,Josep Rizo,Caroline Kisker,Eric C. Greene,Sue Biggins,Scott Keeney,Scott Keeney,Elizabeth A. Miller,J. Christopher Fromme,Tamara L. Hendrickson,Qian Cong,David Baker +31 more
TL;DR: The structures of many eukaryotic protein complexes are unknown, and there are likely many protein-protein interactions not yet identified as mentioned in this paper, but these structures play critical roles in biology.
Journal ArticleDOI
Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.
Ivan Anishchenko,Minkyung Baek,Hahnbeom Park,Naozumi Hiranuma,David E. Kim,Justas Dauparas,Sanaa Mansoor,Ian R. Humphreys,David Baker +8 more
TL;DR: The trRosetta structure prediction method employs deep learning to generate predicted residue-residue distance and orientation distributions from which 3D models are built as mentioned in this paper, and it is faster and requires less computing resources, completing the entire modeling process in a median < 3 h in CASP14.
Journal ArticleDOI
Protein oligomer modeling guided by predicted interchain contacts in CASP14.
TL;DR: In this paper, a deep learning-based method was developed for predicting homo-oligomeric contacts and used them for oligomer modeling, which produced oligomer models with summed Z-scores 5.5 units higher than the next best group, with the fold-and-dock method having the best relative performance.
Posted ContentDOI
Structures of core eukaryotic protein complexes
Ian R. Humphreys,Jimin Pei,Minkyung Baek,Krishnakumar A,Ivan Anishchenko,Sergey Ovchinnikov,Jianhua Zhang,Travis J. Ness,Sudeep Banjade,Saket R. Bagde,Viktoriya G. Stancheva,Xiao-Han Li,Kaixian Liu,Zheng Z,Zheng Z,Barrero Dj,Upasana Roy,Fernández Is,Barnabas Szakal,Dana Branzei,Eric C. Greene,Biggins S,Scott Keeney,Scott Keeney,Elizabeth A. Miller,Fromme Jc,Hendrickson Tl,Qian Cong,David Baker,David Baker +29 more
TL;DR: In this article, a combination of RoseTTAFold and AlphaFold is used to screen through paired multiple sequence alignments for 8.3 million pairs of S. cerevisiae proteins and build models for strongly predicted protein assemblies.