Sayan Mondal

2.4k total citations · 1 hit paper
26 papers, 1.6k citations indexed

About

Sayan Mondal is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics. According to data from OpenAlex, Sayan Mondal has authored 26 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 8 papers in Cellular and Molecular Neuroscience and 4 papers in Computational Theory and Mathematics. Recurrent topics in Sayan Mondal's work include Lipid Membrane Structure and Behavior (11 papers), Receptor Mechanisms and Signaling (11 papers) and Protein Structure and Dynamics (7 papers). Sayan Mondal is often cited by papers focused on Lipid Membrane Structure and Behavior (11 papers), Receptor Mechanisms and Signaling (11 papers) and Protein Structure and Dynamics (7 papers). Sayan Mondal collaborates with scholars based in United States, Ireland and China. Sayan Mondal's co-authors include George Khelashvili, Harel Weinstein, Robert Abel, Richard A. Friesner, Lingle Wang, Wei Chen, Edward Harder, Katarina Roos, Markus K. Dahlgren and James Stevenson and has published in prestigious journals such as Journal of the American Chemical Society, The EMBO Journal and Blood.

In The Last Decade

Sayan Mondal

24 papers receiving 1.6k citations

Hit Papers

OPLS3e: Extending Force Field Coverage for Drug-Like Smal... 2019 2026 2021 2023 2019 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sayan Mondal United States 15 1.1k 367 226 208 144 26 1.6k
Outi M. H. Salo‐Ahen Finland 21 951 0.9× 409 1.1× 218 1.0× 211 1.0× 174 1.2× 48 1.8k
Callum J. Dickson United Kingdom 17 1.6k 1.5× 382 1.0× 250 1.1× 213 1.0× 274 1.9× 24 2.1k
Hui Sun Lee United States 22 1.6k 1.5× 322 0.9× 131 0.6× 310 1.5× 224 1.6× 43 2.3k
Robin M. Betz United States 10 1.6k 1.5× 267 0.7× 528 2.3× 159 0.8× 154 1.1× 16 2.0k
Philip Gribbon Germany 22 739 0.7× 240 0.7× 82 0.4× 194 0.9× 100 0.7× 83 1.5k
Ivanov As Russia 22 944 0.9× 259 0.7× 84 0.4× 172 0.8× 107 0.7× 183 1.8k
Andrew J. Pope United Kingdom 28 1.7k 1.6× 171 0.5× 197 0.9× 297 1.4× 131 0.9× 63 2.4k
Jung‐Hsin Lin Taiwan 24 1.7k 1.6× 585 1.6× 145 0.6× 284 1.4× 217 1.5× 61 2.4k
Allison K. Doak United States 14 1.1k 1.1× 813 2.2× 127 0.6× 251 1.2× 177 1.2× 14 1.8k
Benjamin D. Madej United States 7 1.1k 1.0× 181 0.5× 209 0.9× 132 0.6× 119 0.8× 7 1.4k

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 of co-authors of Sayan Mondal

This figure shows the co-authorship network connecting the top 25 collaborators of Sayan Mondal. A scholar is included among the top collaborators of Sayan Mondal 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 Sayan Mondal. Sayan Mondal 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
2.
Leit, Silvana, Jeremy R. Greenwood, Sayan Mondal, et al.. (2022). Potent and selective TYK2-JH1 inhibitors highly efficacious in rodent model of psoriasis. Bioorganic & Medicinal Chemistry Letters. 73. 128891–128891. 10 indexed citations
5.
Roos, Katarina, Chuanjie Wu, Wolfgang Damm, et al.. (2019). OPLS3e: Extending Force Field Coverage for Drug-Like Small Molecules. Journal of Chemical Theory and Computation. 15(3). 1863–1874. 857 indexed citations breakdown →
6.
Wang, Shenqiu, Sayan Mondal, Chunying Zhao, et al.. (2019). Noncovalent inhibitors reveal BTK gatekeeper and auto-inhibitory residues that control its transforming activity. JCI Insight. 4(12). 24 indexed citations
7.
Mondal, Sayan, et al.. (2019). Channelrhodopsin-2 Function is Modulated by Residual Hydrophobic Mismatch with the Surrounding Lipid Environment. Applied Sciences. 9(13). 2674–2674. 1 indexed citations
8.
Mondal, Sayan, George Khelashvili, & Harel Weinstein. (2014). Not Just an Oil Slick: How the Energetics of Protein-Membrane Interactions Impacts the Function and Organization of Transmembrane Proteins. Biophysical Journal. 106(11). 2305–2316. 46 indexed citations
9.
Mondal, Sayan, Jennifer M. Johnston, Hao Wang, et al.. (2013). Membrane Driven Spatial Organization of GPCRs. Scientific Reports. 3(1). 2909–2909. 91 indexed citations
10.
Mondal, Sayan, George Khelashvili, Lei Shi, & Harel Weinstein. (2013). The cost of living in the membrane: A case study of hydrophobic mismatch for the multi-segment protein LeuT. Chemistry and Physics of Lipids. 169. 27–38. 39 indexed citations
11.
Mondal, Sayan, George Khelashvili, Niklaus Johner, & Harel Weinstein. (2013). How the Dynamic Properties and Functional Mechanisms of GPCRs Are Modulated by Their Coupling to the Membrane Environment. Advances in experimental medicine and biology. 796. 55–74. 19 indexed citations
12.
Mondal, Sayan, George Khelashvili, Hao Wang, et al.. (2012). Interaction with the Membrane Uncovers Essential Differences Between Highly Homologous GPCRs. Biophysical Journal. 102(3). 514a–514a. 2 indexed citations
13.
Khelashvili, George, Sayan Mondal, Martin Caffrey, & Harel Weinstein. (2012). Quantitative Comparison of GPCR Interactions with the Lipid Bilayer of the Cubic and Lamellar Mesophases. Biophysical Journal. 102(3). 467a–468a. 1 indexed citations
14.
Shan, Jufang, George Khelashvili, Sayan Mondal, Ernest L. Mehler, & Harel Weinstein. (2012). Ligand-Dependent Conformations and Dynamics of the Serotonin 5-HT2A Receptor Determine Its Activation and Membrane-Driven Oligomerization Properties. PLoS Computational Biology. 8(4). e1002473–e1002473. 95 indexed citations
15.
Khelashvili, George, Pedro Blecua, Niklaus Johner, et al.. (2012). Why GPCRs behave differently in cubic and lamellar lipidic mesophases. Journal of the American Chemical Society. 134(38). 15858–15868. 43 indexed citations
16.
Shan, Jufang, George Khelashvili, Sayan Mondal, & Harel Weinstein. (2011). Pharmacologically Distinct Ligands Induce Different States of 5-HT2AR and Trigger Different Membrane Remodeling: Implications For GPCR Oligomerization. Biophysical Journal. 100(3). 254a–254a. 3 indexed citations
17.
Mondal, Sayan, George Khelashvili, Jufang Shan, O.S. Andersen, & Harel Weinstein. (2011). Quantitative Modeling of Membrane Deformations by Multihelical Membrane Proteins: Application to G-Protein Coupled Receptors. Biophysical Journal. 101(9). 2092–2101. 70 indexed citations
18.
Mondal, Sayan, et al.. (2009). Effects of gravity and posture on the human cardiovascular system. 40(11). 1196–1204.
19.
Tang, Dalin, Chun Yang, Sayan Mondal, et al.. (2008). A negative correlation between human carotid atherosclerotic plaque progression and plaque wall stress: In vivo MRI-based 2D/3D FSI models. Journal of Biomechanics. 41(4). 727–736. 100 indexed citations
20.
Tang, Dalin, Chun Yang, Joseph D. Petruccelli, et al.. (2007). Quantifying Human Atherosclerotic Plaque Growth Function Using Multi-Year In Vivo MRI and Meshless Local Petrov-Galerkin Method. 106. 546–551. 1 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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