D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Biology and Biochemistry D-index 94 Citations 51,953 265 World Ranking 1264 National Ranking 757

Research.com Recognitions

Awards & Achievements

2014 - ACM Gordon Bell Prize For Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer

2014 - Member of the National Academy of Sciences

2012 - Member of the National Academy of Engineering For the architecture, design, and implementation of the Anton protein-folding supercomputer.

2009 - ACM Gordon Bell Prize For Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer

2007 - Fellow of the American Academy of Arts and Sciences

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Enzyme
  • Programming language

David E. Shaw spends much of his time researching Molecular dynamics, Biophysics, Statistical physics, Protein structure and Protein folding. His Molecular dynamics research is included under the broader classification of Computational chemistry. His Biophysics research also works with subjects such as

  • G protein-coupled receptor that connect with fields like Binding site and Agonist,
  • Allosteric regulation, which have a strong connection to Stereochemistry,
  • Receptor which is related to area like Signal transduction.

David E. Shaw regularly ties together related areas like Force field in his Statistical physics studies. His Protein structure research is multidisciplinary, relying on both ERBB3, Analytical chemistry, Conformational change, Permeation and Cell biology. The various areas that David E. Shaw examines in his Protein folding study include Small peptide, Proteins metabolism and MOLECULAR BIOLOGY METHODS.

His most cited work include:

  • Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. (4754 citations)
  • Improved side‐chain torsion potentials for the Amber ff99SB protein force field (2889 citations)
  • Improved side‐chain torsion potentials for the Amber ff99SB protein force field (2889 citations)

What are the main themes of his work throughout his whole career to date?

David E. Shaw mainly focuses on Molecular dynamics, Biophysics, Parallel computing, Protein structure and Biochemistry. His studies deal with areas such as Chemical physics, Statistical physics and Protein folding as well as Molecular dynamics. He works mostly in the field of Protein folding, limiting it down to concerns involving Biological system and, occasionally, Nanotechnology.

His work deals with themes such as Receptor, Signal transduction, G protein-coupled receptor, Rational design and Binding site, which intersect with Biophysics. His studies in Parallel computing integrate themes in fields like Software, Computation and Latency. As a part of the same scientific study, David E. Shaw usually deals with the Biochemistry, concentrating on Cell biology and frequently concerns with Cell membrane.

He most often published in these fields:

  • Molecular dynamics (47.91%)
  • Biophysics (30.08%)
  • Parallel computing (12.53%)

What were the highlights of his more recent work (between 2017-2021)?

  • Biophysics (30.08%)
  • Molecular dynamics (47.91%)
  • Drug discovery (9.47%)

In recent papers he was focusing on the following fields of study:

David E. Shaw mostly deals with Biophysics, Molecular dynamics, Drug discovery, Intrinsically disordered proteins and Computational biology. His Biophysics research integrates issues from Native state, Kinase and Binding site. The concepts of his Molecular dynamics study are interwoven with issues in Adaptation, Protein protein and Hemagglutinin.

David E. Shaw has included themes like Fragment, Plasma protein binding, Binding properties, Target protein and Small molecule in his Drug discovery study. David E. Shaw interconnects Chemical physics, Molecular recognition and Protein secondary structure in the investigation of issues within Intrinsically disordered proteins. His Protein folding course of study focuses on Protein dynamics and Statistical physics.

Between 2017 and 2021, his most popular works were:

  • Developing a molecular dynamics force field for both folded and disordered protein states. (286 citations)
  • Developing a molecular dynamics force field for both folded and disordered protein states. (286 citations)
  • RNA force field with accuracy comparable to state-of-the-art protein force fields (84 citations)

In his most recent research, the most cited papers focused on:

  • Gene
  • Enzyme
  • Programming language

The scientist’s investigation covers issues in Molecular dynamics, Force field, Biophysics, Protein protein and Chemical physics. His Molecular dynamics research is multidisciplinary, relying on both Intrinsically disordered proteins, Nucleic acid and Protein secondary structure. His study in Intrinsically disordered proteins is interdisciplinary in nature, drawing from both Protein dynamics, Statistical physics and Protein folding.

His Force field study combines topics from a wide range of disciplines, such as RNA and Biological system. David E. Shaw has researched Biophysics in several fields, including Glutamate receptor, NMDA receptor, Kinase and Phosphorylation. The study incorporates disciplines such as Molecular recognition, Protein tertiary structure, Phosphoprotein and Intermolecular force in addition to Chemical physics.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.

Richard A Friesner;Jay L Banks;Robert B Murphy;Thomas A Halgren.
Journal of Medicinal Chemistry (2004)

7670 Citations

Improved side‐chain torsion potentials for the Amber ff99SB protein force field

Kresten Lindorff-Larsen;Stefano Piana;Kim Palmo;Paul Maragakis.
Proteins (2010)

4547 Citations

Atomic-Level Characterization of the Structural Dynamics of Proteins

David E. Shaw;David E. Shaw;Paul Maragakis;Kresten Lindorff-Larsen;Stefano Piana.
Science (2010)

1840 Citations

A hierarchical approach to all-atom protein loop prediction.

Matthew P. Jacobson;David L. Pincus;Chaya S. Rapp;Tyler J.F. Day.
Proteins (2004)

1768 Citations

How Fast-Folding Proteins Fold

Kresten Lindorff-Larsen;Stefano Piana;Ron O. Dror;David E. Shaw;David E. Shaw.
Science (2011)

1753 Citations

Scalable algorithms for molecular dynamics simulations on commodity clusters

Kevin J. Bowers;Edmond Chow;Huafeng Xu;Ron O. Dror.
conference on high performance computing (supercomputing) (2006)

1562 Citations

How robust are protein folding simulations with respect to force field parameterization

Stefano Piana;Kresten Lindorff-Larsen;David E. Shaw;David E. Shaw.
Biophysical Journal (2011)

987 Citations

PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results

Steven L. Dixon;Alexander M. Smondyrev;Eric H. Knoll;Eric H. Knoll;Shashidhar N. Rao.
Journal of Computer-aided Molecular Design (2006)

965 Citations

Biomolecular Simulation: A Computational Microscope for Molecular Biology

Ron O. Dror;Robert M. Dirks;J.P. Grossman;Huafeng Xu.
Annual Review of Biophysics (2012)

958 Citations

Electronic mail system for displaying advertisement at local computer received from remote system while the local computer is off-line the remote system

David E. Shaw;Charles E. Ardai;Brian D. Marsh;Mark A. Moraes.
(1996)

879 Citations

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