Author

Yevgeniy Antipin

Icahn School of Medicine at Mount Sinai

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 2 Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Chris SanderiD· 3 shared Augustin LunaiD· 1 shared Boris A. RevaiD· 1 shared Christian DallagoiD· 1 shared Debora S. MarksiD· 1 shared Drew Diamantoukos· 1 shared Ino de BruijniD· 1 shared Li Yang· 1 shared

Activity by Year

2015-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBioinformatics

Chris SanderORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

MutationAssessor in cBioPortal

Yang Su, Xiang Li, Boris A. Reva, Yevgeniy Antipin, Nikolaus D. Schultz, Ino de Bruijn, Chris Sander

MutationAssessor version 4 provides updated functional impact scores for mutations using expanded data and improved analysis methods, now integrated into cBioPortal.

bioRxiv · Aug 10, 2025 · PreprintCancer Biology

AlignmentViewer: Sequence Analysis of Large Protein Families

Roc Reguant, Yevgeniy Antipin, Rob Sheridan, Christian Dallago, Drew Diamantoukos, Augustin Luna, Chris Sander, Nicholas Paul Gauthier

AlignmentViewer provides a web-based tool for visualizing and analyzing large protein family alignments, supporting evolutionary coupling analysis and 3D structure computation.

F1000Research · Mar 27, 2020Peer-reviewedBioinformatics

EVfold.org: Evolutionary Couplings and Protein 3D Structure Prediction

Robert Sheridan, Robert J. Fieldhouse, Sikander Hayat, Yichao Sun, Yevgeniy Antipin, Li Yang, Thomas Hopf, Debora S. Marks, Chris Sander

EVfold.org uses evolutionary couplings to predict protein 3D structures from sequence data with high accuracy.

bioRxiv · Jul 2, 2015 · PreprintBioinformatics