E. Srinivasan

711 total citations
35 papers, 492 citations indexed

About

E. Srinivasan is a scholar working on Molecular Biology, Neurology and Physiology. According to data from OpenAlex, E. Srinivasan has authored 35 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 16 papers in Neurology and 10 papers in Physiology. Recurrent topics in E. Srinivasan's work include Amyotrophic Lateral Sclerosis Research (13 papers), Alzheimer's disease research and treatments (9 papers) and Cholinesterase and Neurodegenerative Diseases (7 papers). E. Srinivasan is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (13 papers), Alzheimer's disease research and treatments (9 papers) and Cholinesterase and Neurodegenerative Diseases (7 papers). E. Srinivasan collaborates with scholars based in India, United States and Malaysia. E. Srinivasan's co-authors include R. Rajasekaran, G. Chandrasekhar, Rohini Karunakaran, K. Anbarasu, A. S. Vickram, P. S. Srikumar, Rao Sethumadhavan, Nikolay V. Dokholyan, Morgan Chandler and Jian Wang and has published in prestigious journals such as ACS Nano, Journal of Molecular Biology and Chemical Communications.

In The Last Decade

E. Srinivasan

31 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E. Srinivasan India 11 206 199 140 98 73 35 492
Ronit Shaltiel‐Karyo Israel 11 161 0.8× 213 1.1× 232 1.7× 69 0.7× 94 1.3× 14 491
Eugene Huh South Korea 17 96 0.5× 245 1.2× 130 0.9× 93 0.9× 82 1.1× 39 658
Alice Cheng United States 11 110 0.5× 304 1.5× 279 2.0× 90 0.9× 90 1.2× 14 700
Vibha Taneja India 12 107 0.5× 356 1.8× 236 1.7× 57 0.6× 54 0.7× 22 624
Loreto Martínez‐González Spain 15 176 0.9× 255 1.3× 119 0.8× 187 1.9× 84 1.2× 29 576
Kevin J. Barnham Australia 7 227 1.1× 202 1.0× 262 1.9× 33 0.3× 87 1.2× 13 496
Ayşe Ercan Türkiye 14 139 0.7× 206 1.0× 73 0.5× 66 0.7× 78 1.1× 29 626
Mario Caruana Malta 11 308 1.5× 306 1.5× 414 3.0× 103 1.1× 115 1.6× 15 875
Laura Serafina Cerasa Italy 16 98 0.5× 200 1.0× 109 0.8× 118 1.2× 95 1.3× 22 641
Nikolai Lorenzen Denmark 11 342 1.7× 245 1.2× 361 2.6× 38 0.4× 86 1.2× 11 676

Countries citing papers authored by E. Srinivasan

Since Specialization
Citations

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

Fields of papers citing papers by E. Srinivasan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Srinivasan

This figure shows the co-authorship network connecting the top 25 collaborators of E. Srinivasan. A scholar is included among the top collaborators of E. Srinivasan 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 E. Srinivasan. E. Srinivasan 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.
Hnath, Brianna, et al.. (2026). Novel extracellular vesicle release pathway facilitated by toxic superoxide dismutase 1 oligomers. Neurobiology of Disease. 220. 107309–107309.
2.
Srinivasan, E., et al.. (2025). The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives. Journal of Molecular Biology. 437(20). 169060–169060. 3 indexed citations
3.
Srinivasan, E. & Nikolay V. Dokholyan. (2025). Peptide-based drug design using generative AI. Chemical Communications. 62(3). 672–691.
4.
Srinivasan, E., et al.. (2024). Application of Quantum Tensor Networks for Protein Classification. 132–137. 2 indexed citations
5.
6.
Srinivasan, E., G. Chandrasekhar, & R. Rajasekaran. (2022). Probing the polyphenolic flavonoid, morin as a highly efficacious inhibitor against amyloid(A4V) mutant SOD1 in fatal amyotrophic lateral sclerosis. Archives of Biochemistry and Biophysics. 727. 109318–109318. 7 indexed citations
7.
8.
Chandrasekhar, G., et al.. (2021). Molecular simulation probes the potency of resveratrol in regulating the toxic aggregation of mutant V30M TTR fibrils in Transthyretin mediated amyloidosis. Journal of Molecular Graphics and Modelling. 110. 108055–108055. 1 indexed citations
9.
Srinivasan, E., G. Chandrasekhar, K. Anbarasu, et al.. (2021). Decoding Conformational Imprint of Convoluted Molecular Interactions Between Prenylflavonoids and Aggregated Amyloid-Beta42 Peptide Causing Alzheimer’s Disease. Frontiers in Chemistry. 9. 753146–753146. 10 indexed citations
10.
Chandrasekhar, G., et al.. (2021). Molecular simulation unravels the amyloidogenic misfolding of nascent ApoA1 protein, driven by deleterious point mutations occurring in between 170–178 hotspot region. Journal of Biomolecular Structure and Dynamics. 40(23). 13278–13290. 2 indexed citations
11.
Srinivasan, E. & R. Rajasekaran. (2020). A Systematic and Comprehensive Review on Disease-Causing Genes in Amyotrophic Lateral Sclerosis. Journal of Molecular Neuroscience. 70(11). 1742–1770. 18 indexed citations
12.
Srinivasan, E., et al.. (2020). TTRMDB: A database for structural and functional analysis on the impact of SNPs over transthyretin (TTR) using bioinformatic tools. Computational Biology and Chemistry. 87. 107290–107290. 8 indexed citations
13.
Srinivasan, E. & R. Rajasekaran. (2019). Rational design of linear tripeptides against the aggregation of human mutant SOD1 protein causing amyotrophic lateral sclerosis. Journal of the Neurological Sciences. 405. 116425–116425. 11 indexed citations
14.
15.
Srinivasan, E. & R. Rajasekaran. (2018). Molecular binding response of naringin and naringenin to H46R mutant SOD1 protein in combating protein aggregation using density functional theory and discrete molecular dynamics. Progress in Biophysics and Molecular Biology. 145. 40–51. 17 indexed citations
16.
Srinivasan, E. & R. Rajasekaran. (2018). Quantum chemical and molecular mechanics studies on the assessment of interactions between resveratrol and mutant SOD1 (G93A) protein. Journal of Computer-Aided Molecular Design. 32(12). 1347–1361. 25 indexed citations
17.
Srinivasan, E. & R. Rajasekaran. (2017). Computational investigation of the human SOD1 mutant, Cys146Arg, that directs familial amyotrophic lateral sclerosis. Molecular BioSystems. 13(8). 1495–1503. 14 indexed citations
18.
Srinivasan, E., Rao Sethumadhavan, & R. Rajasekaran. (2017). A theoretical study on Zn binding loop mutants instigating destabilization and metal binding loss in human SOD1 protein. Journal of Molecular Modeling. 23(4). 103–103. 5 indexed citations
19.
Srinivasan, E. & R. Rajasekaran. (2017). Probing the inhibitory activity of epigallocatechin-gallate on toxic aggregates of mutant (L84F) SOD1 protein through geometry based sampling and steered molecular dynamics. Journal of Molecular Graphics and Modelling. 74. 288–295. 35 indexed citations
20.

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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