Amar Koleti
Impact in
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- Computational Drug Discovery Methods
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
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- Bioinformatics and Genomic Networks 3
- Biomedical Text Mining and Ontologies 2
- Single-cell and spatial transcriptomics 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Stephan C. Schürer (6 shared papers)D. Vidović (4 shared papers)Caty Chung (4 shared papers)Uma D. Vempati (3 shared papers)Mario Medvedovic (2 shared papers)Daniel J. Cooper (2 shared papers)Avi Ma’ayan (2 shared papers)Raymond Terryn (2 shared papers)
- Journals
- Nucleic Acids Research (2 papers)SLAS DISCOVERY (1 paper)Scientific Data (1 paper)Journal of Biomedical Semantics (1 paper)Frontiers in Genetics (1 paper)
- Partner nations
- United StatesSwedenDenmark
In The Last Decade
Amar Koleti
7 papers receiving 386 citations
Peers
Comparison fields: 5 of 72
- Computational Theory and Mathematics 152
- Biophysics 26
- Molecular Biology 305
- Information Systems and Management 16
- Pharmacology 16
Countries citing papers authored by Amar Koleti
This map shows the geographic impact of Amar Koleti'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 Amar Koleti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amar Koleti more than expected).
Fields of papers citing papers by Amar Koleti
This network shows the impact of papers produced by Amar Koleti. 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 Amar Koleti. The network helps show where Amar Koleti may publish in the future.
Co-authors
The 25 scholars most cited alongside Amar Koleti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 100 | |
| 2 | 2020 | 90 | |
| 3 | 2014 | 56 | |
| 4 | 2014 | 55 | |
| 5 | 2014 | 51 | |
| 6 | 2013 | 20 | |
| 7 | 2018 | 16 |
About Amar Koleti
Amar Koleti is a scholar working on Molecular Biology, Computational Theory and Mathematics, Information Systems and Management, Artificial Intelligence and Pharmacology, having authored 7 papers that have together received 388 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), Bioinformatics and Genomic Networks (3 papers), Biomedical Text Mining and Ontologies (2 papers), Scientific Computing and Data Management (2 papers), Single-cell and spatial transcriptomics (1 paper), Cancer Genomics and Diagnostics (1 paper), Computational Physics and Python Applications (1 paper) and Pharmacogenetics and Drug Metabolism (1 paper). The work is most often cited by research in Computational Theory and Mathematics (152 citations), Biophysics (26 citations), Molecular Biology (305 citations), Information Systems and Management (16 citations) and Pharmacology (16 citations). Amar Koleti has collaborated with scholars based in United States, Sweden and Denmark. Frequent co-authors include Stephan C. Schürer, D. Vidović, Caty Chung, Uma D. Vempati, Mario Medvedovic, Daniel J. Cooper, Avi Ma’ayan, Raymond Terryn, Vasileios Stathias and Alexander Lachmann. Their work appears in journals such as Nucleic Acids Research, SLAS DISCOVERY, Scientific Data, Journal of Biomedical Semantics and Frontiers in Genetics.
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.