Sudipto Mukherjee

2.7k citations
27 papers · 1.9k indexed · 2 hit papers · h-index 17

Sudipto Mukherjee

27 papers receiving 1.9k citations

Hit Papers

DOCK 6: Impact of new features and current docking perfo...5632009202620142020200400600

Peers

Sudipto Mukherjee
Comparison fields: 5 of 138
  • Computational Theory and Mathematics 722
  • Molecular Biology 1.3k
  • Virology 56
  • Pharmacology 148
  • Organic Chemistry 250
Replace P. Therese Lang with:
P. Therese Lang United States
Daniel K. Gehlhaar United States
Friedrich Rippmann Germany
Trent E. Balius United States
Zukang Feng United States
Gregory Sliwoski United States
Ángel R. Ortíz Spain
Scott R. Brozell United States
Andrea Volkamer Germany
Vinícius Gonçalves Maltarollo Brazil
Sudipto Mukherjee relative to P. Therese Lang United States P. Therese Lang's profile →
Citations per field
00.5×1.5×
P. Therese Lang · 1×
Citations per year

Countries citing papers authored by Sudipto Mukherjee

Since Specialization
Citations

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

Fields of papers citing papers by Sudipto Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Sudipto Mukherjee, 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 Sudipto Mukherjee Line = papers co-authored together Sudipto Mukherjee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20211
3
C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation
20201
4 202059
5 201725
6 201716
7 201761
8 20173
9 20171
10 201618
11 201523
12 201538
13 201422
14 201325
15 2012130
16 201154
17 2010176
18
DOCK 6: Combining techniques to model RNA–small molecule complexesbreakdown →
2009603
19
Voice over IP Fundamentals (2nd Edition) (Fundamentals)
20067
20 19585

About Sudipto Mukherjee

Sudipto Mukherjee is a scholar working on Virology, Computational Theory and Mathematics and Molecular Biology, having authored 27 papers that have together received 1.9k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Computational Drug Discovery Methods (6 papers), HIV Research and Treatment (3 papers), DNA and Nucleic Acid Chemistry (3 papers), Enzyme Structure and Function (3 papers), Chemical Synthesis and Analysis (2 papers), Distributed Control Multi-Agent Systems (2 papers) and Receptor Mechanisms and Signaling (2 papers). The work is most often cited by research in Computational Theory and Mathematics (722 citations), Molecular Biology (1.3k citations) and Virology (56 citations). Sudipto Mukherjee has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Robert C. Rizzo, Trent E. Balius, Scott R. Brozell, David A. Case, P. Therese Lang, Irwin D. Kuntz, William J. Allen, Thomas Leroy James, Elaine C. Meng and Eric F. Pettersen. Their work appears in journals such as Journal of Computational Chemistry, Scientific Reports, Information Sciences, Journal of the American Chemical Society and BMC Bioinformatics.

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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