Gregory R. Bowman

Molecular Biology · 2009–2023

A researcher in the Science corpus: 9 papers; trusts 9 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 107 citations into it; #2,224 of 17,773 by trust here, #4,132 by citations
• Materials Chemistry — 35 citations into it; #2,231 of 11,513 by trust here, #5,575 by citations
• Spectroscopy — 32 citations into it; #392 of 1,674 by trust here, #284 by citations
• Computational Biology & Bioinformatics — 20 citations into it
• Computational Theory and Mathematics — 15 citations into it
• Atomic and Molecular Physics, and Optics — 14 citations into it
• Algorithms & Complexity — 5 citations into it

Whom Gregory R. Bowman trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Christof Schutte
2. Marcus Weber
3. Vijay S. Pande
4. Peter Deuflhard
5. Teofilo F. Gonzalez
6. Michele Parrinello
7. Kyle A. Beauchamp
8. John D. Chodera
9. Alexander Fischer
10. Ken A. Dill

Who trusts Gregory R. Bowman overall

1. Hao Wu
2. Frank No'e
3. Andreas Mardt
4. Wei Wang
5. Vijay S. Pande
6. Luca Pasquali
7. Artur Meller
8. John D. Chodera
9. Kai J. Kohlhoff
10. Brooke E. Husic

Papers from Gregory R. Bowman's perspective

Ordered by how strongly the researchers Gregory R. Bowman trusts endorse each paper. Same corpus, a different order for every researcher.

1. Markov models of molecular kinetics: generation and validation.
2. Protein data bank
3. Anton, a special-purpose machine for molecular dynamics simulation
4. Development and testing of a general amber force field
5. OPM: Orientations of Proteins in Membranes database
6. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers
7. Everything you wanted to know about Markov State Models but were afraid to ask (Methods)
8. Comparison of simple potential functions for simulating liquid water
9. MapReduce: simplified data processing on large clusters
10. An invariant form for the prior probability in estimation problems

Their papers

• Enhanced modeling via network theory: Adaptive sampling of Markov state models (2010) — 244 citations
• Progress and challenges in the automated construction of Markov state models for full protein systems. (2009) — 390 citations
• An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation (2014) — 561 citations
• MSMBuilder2: Modeling Conformational Dynamics at the Picosecond to Millisecond Scale (2011) — 380 citations
• Everything you wanted to know about Markov State Models but were afraid to ask (2010) — 663 citations
• Using generalized ensemble simulations and Markov state models to identify conformational states (2009) — 294 citations
• Predicting the locations of cryptic pockets from single protein structures using the PocketMiner graph neural network (2022) — 69 citations
• Cloud-based simulations on Google Exacycle reveal ligand-modulation of GPCR activation pathways (2013) — 405 citations
• Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network (2023) — 109 citations