David E. Shaw

61.1k total citations · 22 hit papers
282 papers, 43.5k citations indexed

About

David E. Shaw is a scholar working on Molecular Biology, Materials Chemistry and Oncology. According to data from OpenAlex, David E. Shaw has authored 282 papers receiving a total of 43.5k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Molecular Biology, 33 papers in Materials Chemistry and 31 papers in Oncology. Recurrent topics in David E. Shaw's work include Protein Structure and Dynamics (50 papers), Enzyme Structure and Function (28 papers) and Receptor Mechanisms and Signaling (25 papers). David E. Shaw is often cited by papers focused on Protein Structure and Dynamics (50 papers), Enzyme Structure and Function (28 papers) and Receptor Mechanisms and Signaling (25 papers). David E. Shaw collaborates with scholars based in United States, United Kingdom and Australia. David E. Shaw's co-authors include Ron O. Dror, Stefano Piana, Kresten Lindorff‐Larsen, John L. Klepeis, Paul Maragakis, Richard A. Friesner, Yibing Shan, Michael P. Eastwood, Huafeng Xu and Kim Palmö and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

David E. Shaw

273 papers receiving 42.8k citations

Hit Papers

Glide:  A New Approach for Rapid, Accurate Docking and Sc... 2004 2026 2011 2018 2004 2010 2006 2004 2011 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Glide:  A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy
    2004 7.6k citations Richard A. Friesner, Jay L. Banks et al. Journal of Medicinal Chemistry profile →
  2. Improved side‐chain torsion potentials for the Amber ff99SB protein force field
    2010 4.7k citations Stefano Piana, Paul Maragakis et al. profile →
  3. Molecular dynamics---Scalable algorithms for molecular dynamics simulations on commodity clusters
    2006 1.9k citations K. J. Bowers, Federico D. Sacerdoti et al. profile →
  4. A hierarchical approach to all‐atom protein loop prediction
    2004 1.9k citations David E. Shaw, Richard A. Friesner et al. profile →
  5. How Fast-Folding Proteins Fold
    2011 1.5k citations Stefano Piana, Ron O. Dror et al. Science profile →
  6. Atomic-Level Characterization of the Structural Dynamics of Proteins
    2010 1.4k citations David E. Shaw, Paul Maragakis et al. Science profile →
  7. Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters
    2006 1.2k citations K. J. Bowers, Huafeng Xu et al. profile →
  8. PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results
    2006 947 citations David E. Shaw, Richard A. Friesner et al. profile →
  9. Biomolecular Simulation: A Computational Microscope for Molecular Biology
    2012 856 citations Ron O. Dror, Robert M. Dirks et al. profile →
  10. Developing a molecular dynamics force field for both folded and disordered protein states
    2018 736 citations Paul Robustelli, Stefano Piana et al. Proceedings of the National Academy of Sciences profile →
  11. Structure and dynamics of the M3 muscarinic acetylcholine receptor
    2012 648 citations Albert C. Pan, Daniel H. Arlow et al. profile →
  12. The Dynamic Process of β2-Adrenergic Receptor Activation
    2013 646 citations Ron O. Dror, Thomas J. Mildorf et al. profile →
  13. Structure and function of an irreversible agonist-β2 adrenoceptor complex
    2011 643 citations Daniel H. Arlow, Roger K. Sunahara et al. profile →
  14. Water Dispersion Interactions Strongly Influence Simulated Structural Properties of Disordered Protein States
    2015 626 citations Stefano Piana, Paul Robustelli et al. profile →
  15. Pathway and mechanism of drug binding to G-protein-coupled receptors
    2011 594 citations Ron O. Dror, Albert C. Pan et al. Proceedings of the National Academy of Sciences profile →
  16. Long-timescale molecular dynamics simulations of protein structure and function
    2009 578 citations John L. Klepeis, Ron O. Dror et al. profile →
  17. Systematic Validation of Protein Force Fields against Experimental Data
    2012 538 citations Paul Maragakis, Stefano Piana et al. profile →
  18. Activation mechanism of theβ2-adrenergic receptor
    2011 484 citations Ron O. Dror, Daniel H. Arlow et al. Proceedings of the National Academy of Sciences profile →
  19. How Does a Drug Molecule Find Its Target Binding Site?
    2011 484 citations Yibing Shan, Eric T. Kim et al. profile →
  20. High-resolution crystal structure of human protease-activated receptor 1
    2012 361 citations Yoga Srinivasan, Daniel H. Arlow et al. profile →
  21. Oncogenic Mutations Counteract Intrinsic Disorder in the EGFR Kinase and Promote Receptor Dimerization
    2012 276 citations Yibing Shan, Michael P. Eastwood et al. profile →
  22. Structural mechanism of a drug-binding process involving a large conformational change of the protein target
    2023 59 citations Markus A. Seeliger, Yibing Shan et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David E. Shaw United States 85 29.5k 7.8k 6.1k 4.4k 4.2k 282 43.5k
Junmei Wang China 67 25.1k 0.8× 7.7k 1.0× 7.1k 1.2× 2.5k 0.6× 3.2k 0.8× 416 45.8k
Thomas E. Ferrin United States 43 35.6k 1.2× 4.6k 0.6× 5.5k 0.9× 2.4k 0.6× 5.0k 1.2× 93 55.6k
Elaine C. Meng United States 29 32.3k 1.1× 4.1k 0.5× 4.9k 0.8× 2.7k 0.6× 3.5k 0.8× 35 50.0k
Andrej Săli United States 107 50.4k 1.7× 4.8k 0.6× 11.4k 1.9× 3.8k 0.9× 4.5k 1.1× 381 66.1k
Ruth Nussinov United States 112 44.1k 1.5× 9.9k 1.3× 10.6k 1.7× 1.8k 0.4× 3.5k 0.8× 795 54.6k
Jeremy C. Smith United States 92 32.0k 1.1× 3.3k 0.4× 7.8k 1.3× 2.8k 0.6× 4.2k 1.0× 848 58.8k
Conrad C. Huang United States 31 31.3k 1.1× 3.4k 0.4× 4.9k 0.8× 2.3k 0.5× 4.4k 1.1× 48 49.3k
Eric F. Pettersen United States 13 31.0k 1.1× 3.6k 0.5× 4.7k 0.8× 2.2k 0.5× 3.4k 0.8× 15 48.2k
Barry Honig United States 108 37.5k 1.3× 3.8k 0.5× 9.0k 1.5× 6.0k 1.4× 2.3k 0.6× 347 51.3k
Tom Darden United States 28 33.8k 1.1× 4.4k 0.6× 9.7k 1.6× 2.4k 0.5× 3.0k 0.7× 49 55.7k

Countries citing papers authored by David E. Shaw

Since Specialization
Citations

This map shows the geographic impact of David E. Shaw's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David E. Shaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David E. Shaw more than expected).

Fields of papers citing papers by David E. Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Shaw. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David E. Shaw. The network helps show where David E. Shaw may publish in the future.

Co-authorship network of co-authors of David E. Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of David E. Shaw. A scholar is included among the top collaborators of David E. Shaw based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David E. Shaw. David E. Shaw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Adamopoulos, Christos, Tamer A. Ahmed, Maxwell R. Tucker, et al.. (2021). Exploiting Allosteric Properties of RAF and MEK Inhibitors to Target Therapy-Resistant Tumors Driven by Oncogenic BRAF Signaling. Cancer Discovery. 11(7). 1716–1735. 40 indexed citations
2.
Mysore, Venkatesh, Zhi-Wei Zhou, Chiara Ambrogio, et al.. (2021). A structural model of a Ras–Raf signalosome. Nature Structural & Molecular Biology. 28(10). 847–857. 44 indexed citations
3.
Clark, Daniel E., et al.. (2021). Using Machine Learning Methods to Predict the Movement Trajectories of the Louisiana Black Bear. SMU Scholar (Southern Methodist University). 5(1). 11. 1 indexed citations
4.
Jensen, Morten Ø., Fabrizio Giordanetto, Vishwanath Jogini, et al.. (2021). Suppressing Kv1.3 Ion Channel Activity with a Novel Small Molecule Inhibitor Ameliorates Inflammation in a Humanised Mouse Model of Ulcerative Colitis. Journal of Crohn s and Colitis. 15(11). 1943–1958. 13 indexed citations
5.
Pan, Albert C., et al.. (2019). Atomic-level characterization of protein–protein association. Proceedings of the National Academy of Sciences. 116(10). 4244–4249. 148 indexed citations
6.
Wang, Qi, et al.. (2019). Structural mechanism for Bruton’s tyrosine kinase activation at the cell membrane. Proceedings of the National Academy of Sciences. 116(19). 9390–9399. 48 indexed citations
7.
Tan, Dazhi, Stefano Piana, Robert M. Dirks, & David E. Shaw. (2018). RNA force field with accuracy comparable to state-of-the-art protein force fields. Proceedings of the National Academy of Sciences. 115(7). E1346–E1355. 202 indexed citations
8.
Robustelli, Paul, Stefano Piana, & David E. Shaw. (2018). Developing a molecular dynamics force field for both folded and disordered protein states. Proceedings of the National Academy of Sciences. 115(21). E4758–E4766. 736 indexed citations breakdown →
9.
Bokoch, Michael P., Hyunil Jo, James R. Valcourt, et al.. (2018). Entry from the Lipid Bilayer: A Possible Pathway for Inhibition of a Peptide G Protein-Coupled Receptor by a Lipophilic Small Molecule. Biochemistry. 57(39). 5748–5758. 22 indexed citations
10.
Dror, Ron O., Thomas J. Mildorf, Daniel Hilger, et al.. (2015). Structural basis for nucleotide exchange in heterotrimeric G proteins. Science. 348(6241). 1361–1365. 216 indexed citations
11.
Arkhipov, Anton, Yibing Shan, Eric T. Kim, Ron O. Dror, & David E. Shaw. (2013). Her2 activation mechanism reflects evolutionary preservation of asymmetric ectodomain dimers in the human EGFR family. eLife. 2. e00708–e00708. 65 indexed citations
12.
Dror, Ron O., Albert C. Pan, Daniel H. Arlow, et al.. (2011). Pathway and mechanism of drug binding to G-protein-coupled receptors. Proceedings of the National Academy of Sciences. 108(32). 13118–13123. 594 indexed citations breakdown →
13.
Tu, Tiankai, Charles A. Rendleman, Patrick J. O. Miller, et al.. (2010). Accelerating parallel analysis of scientific simulation data via Zazen. File and Storage Technologies. 10–10. 18 indexed citations
14.
Seeliger, Markus A., Pratistha Ranjitkar, Corynn Kasap, et al.. (2009). Equally Potent Inhibition of c-Src and Abl by Compounds that Recognize Inactive Kinase Conformations. Cancer Research. 69(6). 2384–2392. 127 indexed citations
15.
Shan, Yibing, Markus A. Seeliger, Michael P. Eastwood, et al.. (2008). A conserved protonation-dependent switch controls drug binding in the Abl kinase. Proceedings of the National Academy of Sciences. 106(1). 139–144. 216 indexed citations
16.
Tu, Tiankai, Charles A. Rendleman, David W. Borhani, et al.. (2008). A scalable parallel framework for analyzing terascale molecular dynamics simulation trajectories. IEEE International Conference on High Performance Computing, Data, and Analytics. 56. 36 indexed citations
17.
Arkin, Isaiah T., Huafeng Xu, Morten Ø. Jensen, et al.. (2007). Mechanism of Na + /H + Antiporting. Science. 317(5839). 799–803. 124 indexed citations
18.
Friesner, Richard A., Jay L. Banks, Robert B. Murphy, et al.. (2004). Glide:  A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy. Journal of Medicinal Chemistry. 47(7). 1739–1749. 7559 indexed citations breakdown →
19.
Shaw, David E., et al.. (1987). The prospects for rainfall modification in the eastern South Island, New Zealand. New Zealand Journal of Geology and Geophysics. 30(2). 189–194.
20.
Shaw, David E., et al.. (1981). The NON-VON Database Machine: A Brief Overview.. IEEE Data(base) Engineering Bulletin. 4(2). 41–52. 27 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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