Rosetta Refinement
Rosetta Refinement is a computational method in structural biology that belongs to the class of protein structure prediction and modeling techniques, distinguished by its integration of fragment-based sampling, all-atom energy minimization, and knowledge-based scoring functions within the Rosetta software suite to iteratively improve macromolecular structural models toward atomic-level accuracy.
136
Publications
20K
Citations
504
Authors
206
Institutions
Publications per year
2017–2026
50
Parents
136
Elmar Krieger, Keehyoung Joo, Jinwoo Lee et al. · Proteins Structure Function and Bioinformatics · 2009 · 1.4K citations · Full text
Automated Structure Solution With autoSHARP
Clemens Vonrhein, Eric Blanc, Pietro Roversi et al. · Humana Press eBooks · 2006 · 971 citations
Life Sciences, Computer Science, Computational Chemistry +13
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504
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206
University of Washington
Seattle, United States
36 h-index
218 publications
54.4K citations

Howard Hughes Medical Institute
Chevy Chase, United States
23 h-index
47 publications
10.8K citations

Johns Hopkins University
Baltimore, United States
13 h-index
56 publications
10.3K citations

Vanderbilt University
Nashville, United States
13 h-index
45 publications
2.2K citations
Stanford University
Stanford, United States
9 h-index
32 publications
4.4K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
9 h-index
21 publications
5.1K citations
University of California, San Francisco
San Francisco, United States
8 h-index
24 publications
7.1K citations
New York University
New York, United States
7 h-index
27 publications
4.3K citations
1–8 of 206
27 publications · 4.1K citations
22
h-index
JCTC · 10 publications · 2.7K citations
10
h-index
9 publications · 1.1K citations
9
h-index
JACS · 7 publications · 574 citations
7
h-index
Repository · 6 publications · 177 citations
6
h-index
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