Vishal B. Siramshetty

1.4k total citations
24 papers, 848 citations indexed

About

Vishal B. Siramshetty is a scholar working on Computational Theory and Mathematics, Molecular Biology and Spectroscopy. According to data from OpenAlex, Vishal B. Siramshetty has authored 24 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computational Theory and Mathematics, 12 papers in Molecular Biology and 6 papers in Spectroscopy. Recurrent topics in Vishal B. Siramshetty's work include Computational Drug Discovery Methods (20 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and Machine Learning in Materials Science (5 papers). Vishal B. Siramshetty is often cited by papers focused on Computational Drug Discovery Methods (20 papers), Metabolomics and Mass Spectrometry Studies (5 papers) and Machine Learning in Materials Science (5 papers). Vishal B. Siramshetty collaborates with scholars based in United States, Germany and Denmark. Vishal B. Siramshetty's co-authors include Robert Preißner, Malgorzata N. Drwal, Björn-Oliver Gohlke, Janette Nickel, Ðắc-Trung Nguyễn, Noel Southall, Ewy A. Mathé, Anton Simeonov, Qiaofeng Chen and Xin Xu and has published in prestigious journals such as Nucleic Acids Research, Scientific Reports and Drug Discovery Today.

In The Last Decade

Vishal B. Siramshetty

24 papers receiving 826 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vishal B. Siramshetty United States 16 488 443 108 88 67 24 848
Alex. M. Weir United Kingdom 2 371 0.8× 424 1.0× 151 1.4× 74 0.8× 62 0.9× 2 956
Xichen Lian China 10 269 0.6× 507 1.1× 100 0.9× 47 0.5× 60 0.9× 14 864
Huidong Yu China 18 300 0.6× 489 1.1× 91 0.8× 69 0.8× 83 1.2× 37 1.0k
Sampada A. Shahane United States 11 304 0.6× 312 0.7× 50 0.5× 83 0.9× 46 0.7× 13 595
Nikolay Savchuk United States 16 569 1.2× 460 1.0× 132 1.2× 134 1.5× 65 1.0× 31 911
Britta Nisius Germany 11 467 1.0× 428 1.0× 50 0.5× 84 1.0× 76 1.1× 18 613
Chuipu Cai China 14 285 0.6× 324 0.7× 128 1.2× 36 0.4× 117 1.7× 28 618
Jianlong Peng China 12 281 0.6× 390 0.9× 84 0.8× 38 0.4× 78 1.2× 14 688
Filip Miljković Germany 16 554 1.1× 460 1.0× 71 0.7× 163 1.9× 91 1.4× 43 806
Xinbin Zhao China 10 525 1.1× 735 1.7× 65 0.6× 143 1.6× 40 0.6× 18 1.0k

Countries citing papers authored by Vishal B. Siramshetty

Since Specialization
Citations

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

Fields of papers citing papers by Vishal B. Siramshetty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vishal B. Siramshetty. 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 Vishal B. Siramshetty. The network helps show where Vishal B. Siramshetty may publish in the future.

Co-authorship network of co-authors of Vishal B. Siramshetty

This figure shows the co-authorship network connecting the top 25 collaborators of Vishal B. Siramshetty. A scholar is included among the top collaborators of Vishal B. Siramshetty 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 Vishal B. Siramshetty. Vishal B. Siramshetty 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.
Shah, Pranav, Vishal B. Siramshetty, Ewy A. Mathé, & Xin Xu. (2024). Developing Robust Human Liver Microsomal Stability Prediction Models: Leveraging Inter-Species Correlation with Rat Data. Pharmaceutics. 16(10). 1257–1257. 1 indexed citations
2.
Siramshetty, Vishal B., Xin Xu, & Pranav Shah. (2023). Artificial Intelligence in ADME Property Prediction. Methods in molecular biology. 2714. 307–327. 7 indexed citations
3.
4.
Siramshetty, Vishal B., J. W. Williams, Md Kabir, et al.. (2023). Development and validation of PAMPA-BBB QSAR model to predict brain penetration potential of novel drug candidates. Frontiers in Pharmacology. 14. 1291246–1291246. 17 indexed citations
5.
Moudgal, Chandrika, Lennart T. Anger, Wolfgang Muster, et al.. (2023). The application of acute oral toxicity computational models in dangerous goods classification. Toxicology and Industrial Health. 39(12). 687–699. 5 indexed citations
6.
Kelleher, Keith J., Timothy Sheils, Stephen L. Mathias, et al.. (2022). Pharos 2023: an integrated resource for the understudied human proteome. Nucleic Acids Research. 51(D1). D1405–D1416. 50 indexed citations
7.
Zahoránszky-Köhalmi, Gergely, Vishal B. Siramshetty, Praveen Kumar, et al.. (2022). A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research. Journal of Chemical Information and Modeling. 62(3). 718–729. 4 indexed citations
8.
Williams, J. W., Vishal B. Siramshetty, Ðắc-Trung Nguyễn, et al.. (2022). Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability. Bioorganic & Medicinal Chemistry. 56. 116588–116588. 32 indexed citations
9.
Siramshetty, Vishal B., Ivan Grishagin, Ðắc-Trung Nguyễn, et al.. (2021). NCATS Inxight Drugs: a comprehensive and curated portal for translational research. Nucleic Acids Research. 50(D1). D1307–D1316. 36 indexed citations
10.
Siramshetty, Vishal B., J. W. Williams, Ðắc-Trung Nguyễn, et al.. (2021). Validating ADME QSAR Models Using Marketed Drugs. SLAS DISCOVERY. 26(10). 1326–1336. 27 indexed citations
11.
Jain, Sankalp, Vishal B. Siramshetty, Vinícius M. Alves, et al.. (2021). Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods. Journal of Chemical Information and Modeling. 61(2). 653–663. 55 indexed citations
12.
Sheils, Timothy, Stephen L. Mathias, Keith J. Kelleher, et al.. (2020). TCRD and Pharos 2021: mining the human proteome for disease biology. Nucleic Acids Research. 49(D1). D1334–D1346. 90 indexed citations
13.
Sheils, Timothy, Stephen L. Mathias, Vishal B. Siramshetty, et al.. (2020). How to Illuminate the Druggable Genome Using Pharos. Current Protocols in Bioinformatics. 69(1). e92–e92. 25 indexed citations
14.
Siramshetty, Vishal B., Pranav Shah, Edward H. Kerns, et al.. (2020). Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models. Scientific Reports. 10(1). 20713–20713. 25 indexed citations
15.
Shah, Pranav, Vishal B. Siramshetty, Alexey Zakharov, et al.. (2020). Predicting liver cytosol stability of small molecules. Journal of Cheminformatics. 12(1). 21–21. 25 indexed citations
16.
Preißner, Saskia, et al.. (2018). Pain-Prescription Differences - An Analysis of 500,000 Discharge Summaries. PubMed. 11(1). 58–66. 8 indexed citations
17.
Siramshetty, Vishal B., Björn-Oliver Gohlke, Andrean Goede, et al.. (2017). SuperDRUG2: a one stop resource for approved/marketed drugs. Nucleic Acids Research. 46(D1). D1137–D1143. 67 indexed citations
18.
Siramshetty, Vishal B. & Robert Preißner. (2017). Drugs as habitable planets in the space of dark chemical matter. Drug Discovery Today. 23(3). 481–486. 6 indexed citations
19.
Banerjee, Priyanka, Vishal B. Siramshetty, Malgorzata N. Drwal, & Robert Preißner. (2016). Computational methods for prediction of in vitro effects of new chemical structures. Journal of Cheminformatics. 8(1). 51–51. 41 indexed citations
20.
Siramshetty, Vishal B., et al.. (2015). WITHDRAWN—a resource for withdrawn and discontinued drugs. Nucleic Acids Research. 44(D1). D1080–D1086. 204 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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