Sayan Mondal

2.4k citations
26 papers · 1.6k indexed · 1 hit paper · h-index 15

Sayan Mondal

24 papers receiving 1.6k citations

Hit Papers

OPLS3e: Extending Force Field Coverage for Drug-Like Smal...8572019202620212023250500750

Peers

Sayan Mondal
Comparison fields: 5 of 122
  • Computational Theory and Mathematics 367
  • Molecular Biology 1.1k
  • Cellular and Molecular Neuroscience 226
  • Toxicology 27
  • Organic Chemistry 208
Replace Hui Sun Lee with:
Hui Sun Lee United States
Callum J. Dickson United Kingdom
Marcel Bermúdez Germany
Irina S. Moreira Portugal
Kunqian Yu China
Mattia Sturlese Italy
Gregory A. Ross United States
Robin M. Betz United States
Boris Aguilar United States
Sayan Mondal relative to Hui Sun Lee United States Hui Sun Lee's profile →
Citations per field
00.5×1.7×
Hui Sun Lee · 1×
Citations per year

Countries citing papers authored by Sayan Mondal

Since Specialization
Citations

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

Fields of papers citing papers by Sayan Mondal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20260
2 202210
3 202118
4
OPLS3e: Extending Force Field Coverage for Drug-Like Small Moleculesbreakdown →
2019857
5 201924
6 201647
7 201446
8 201339
9 201319
10 201391
11 20122
12 20121
13 201295
14 201243
15 201170
16 20113
17 201027
18 20090
19 2008100
20 20071

About Sayan Mondal

Sayan Mondal is a scholar working on Cellular and Molecular Neuroscience, Genetics and Computational Theory and Mathematics, having authored 26 papers that have together received 1.6k indexed citations. Recurring topics across this work include Lipid Membrane Structure and Behavior (11 papers), Receptor Mechanisms and Signaling (11 papers), Protein Structure and Dynamics (7 papers), Computational Drug Discovery Methods (4 papers), Neuropeptides and Animal Physiology (4 papers), Photoreceptor and optogenetics research (2 papers), Chronic Lymphocytic Leukemia Research (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Computational Theory and Mathematics (367 citations), Molecular Biology (1.1k citations) and Cellular and Molecular Neuroscience (226 citations). Sayan Mondal has collaborated with scholars based in United States, Ireland and China. Frequent co-authors include Harel Weinstein, George Khelashvili, Robert Abel, Richard A. Friesner, Lingle Wang, Chuanjie Wu, Wei Chen, James Stevenson, Edward Harder and Markus K. Dahlgren. Their work appears in journals such as Biophysical Journal, Journal of the American Chemical Society, Blood, Journal of Chemical Theory and Computation and Current Opinion in Structural Biology.

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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