Matthew J. O’Meara
Molecular Biology · 2013–2020
A researcher in the Science corpus: 7 papers; trusts 6 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 217 citations into it; #11,592 of 17,773 by trust here, #1,857 by citations
- Materials Chemistry — 97 citations into it; #8,590 of 11,513 by trust here, #2,815 by citations
- Computational Biology & Bioinformatics — 44 citations into it
- Artificial Intelligence — 8 citations into it
Whom Matthew J. O’Meara trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Baker
- Hadley Wickham
- Roland L. Dunbrack
- Tanja Kortemme
- Manfred J. Sippl
- Andrew Leaver-Fay
- Brian Kuhlman
- K. Simons
- Jay W. Ponder
- Martin Karplus
Who trusts Matthew J. O’Meara overall
- B. Coventry
- Jianfu Zhou
- Shane Ó Conchúir
- Craig O. Mackenzie
- Rebecca F. Alford
- David Baker
- Jiaxiang Wu
- Santrupti Nerli
- Tanja Kortemme
- Brian D. Weitzner
Papers from Matthew J. O’Meara's perspective
Ordered by how strongly the researchers Matthew J. O’Meara trusts endorse each paper. Same corpus, a different order for every researcher.
- Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes.
- Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins.
- Alternate states of proteins revealed by detailed energy landscape mapping
- Accurate Bond and Angle Parameters for X-ray Protein Structure Refinement
- Native protein sequences are close to optimal for their structures.
- A simple physical model for binding energy hot spots in protein–protein complexes
- Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions.
- Energy functions that discriminate X-ray and near native folds from well-constructed decoys.
- Estimation of effective interresidue contact energies from protein crystal structures: quasi-chemical approximation
- Generalized born models of macromolecular solvation effects. (Annual review of physical chemistry (Print))
Their papers
- The Rosetta all-atom energy function for macromolecular modeling and design (2017) — 1,486 citations
- Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement (2013) — 199 citations
- A Combined Covalent-Electrostatic Model of Hydrogen Bonding Improves Structure Prediction with Rosetta (2015) — 233 citations
- Ultra-large library docking for discovering new chemotypes (2019) — 846 citations
- A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing (2020) — 3,895 citations
- A Web Resource for Standardized Benchmark Datasets, Metrics, and Rosetta Protocols for Macromolecular Modeling and Design (2015) — 82 citations
- Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. (2020) — 659 citations