Andrew Dalke

74.9k citations
15 papers · 58.4k · 3 hit papers · h-index 10

Impact in

Papers in

Andrew Dalke

15 papers receiving 57.9k citations

Andrew Dalke's Hit Papers

rdkit/rdkit: 2025_03_6 (Q1 2025) Release 2025 · 100 citations
1000+10+20Years since publication10.0k20.0k30.0k40.0k50.0k

Peers

Andrew Dalke
Comparison fields: 5 of 210
  • Molecular Biology 26.7k
  • Physical and Theoretical Chemistry 3.5k
  • Materials Chemistry 13.3k
  • Organic Chemistry 7.6k
  • Catalysis 1.9k
Replace William Humphrey with:
William Humphrey United States
David van der Spoel Sweden
Erik Lindahl Sweden
Kenneth M. Merz United States
Lee G. Pedersen United States
Tom Darden United States
Jayaraman Chandrasekhar India
Wilfred F. van Gunsteren Switzerland
Piotr Cieplak United States
Julian Tirado‐Rives United States
Andrew Dalke relative to William Humphrey United States William Humphrey's profile →
Citations per field
00.5×1.5×
William Humphrey · 1×
Citations per year

Countries citing papers authored by Andrew Dalke

Since Specialization
Citations

This map shows the geographic impact of Andrew Dalke'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 Andrew Dalke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Dalke more than expected).

Fields of papers citing papers by Andrew Dalke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Dalke. 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 Andrew Dalke. The network helps show where Andrew Dalke may publish in the future.

Co-authors

The 25 scholars most cited alongside Andrew Dalke, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andrew Dalke Line = papers co-authored together Andrew Dalke links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
VMD: Visual molecular dynamics
Hit paper breakdown →
199653911
2
Biopython: freely available Python tools for computational molecular biology and bioinformatics
Hit paper breakdown →
20093678
3 1996463
4
rdkit/rdkit: 2025_03_6 (Q1 2025) Release
Hit paper breakdown →
2025100
5 201875
6 199545
7 201935
8 201334
9 201316
10 200211
11 19956
12
Using Tcl for molecular visualization and analysis.
19975
13
NAMD Version 2.4
20023
14 20201
15 20081

About Andrew Dalke

Andrew Dalke is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Spectroscopy and Computer Networks and Communications, having authored 15 papers that have together received 58.4k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (5 papers), Enzyme Structure and Function (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Analytical Chemistry and Chromatography (2 papers), Machine Learning in Materials Science (2 papers), Electrowetting and Microfluidic Technologies (1 paper) and Fluorine in Organic Chemistry (1 paper). The work is most often cited by research in Molecular Biology (26.7k citations), Physical and Theoretical Chemistry (3.5k citations), Materials Chemistry (13.3k citations), Organic Chemistry (7.6k citations) and Catalysis (1.9k citations). Andrew Dalke has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Klaus Schulten, William Humphrey, Jeffrey T. Chang, Thomas Hamelryck, Frank Kauff, Bartek Wilczyński, Cymon J. Cox, Peter Cock, Tiago Antão and Brad Chapman. Their work appears in journals such as Journal of Cheminformatics, Bioinformatics, Computer Physics Communications, Journal of Chemical Information and Modeling and Chemistry Central Journal.

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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