Harish Shankaran
- Hematology top 5%
- Platelet Disorders and Treatments 6
- Immunology and Allergy top 10%
- Biophysics top 5%
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- Gene Regulatory Network Analysis 6
- Glycosylation and Glycoproteins Research 3
- Protein Kinase Regulation and GTPase Signaling 3
- Cell Biology top 10%
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- HER2/EGFR in Cancer Research 8
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- Monoclonal and Polyclonal Antibodies Research 8
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- Blood properties and coagulation 7
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- Computational Drug Discovery Methods 3
- Co-authors
- Sriram NeelameghamH WileyHaluk ResatPaschalis AlexandridisLee K. OpreskoWilliam ChrislerNikki BollingerDanielle L. Ippolito
- Journals
- PLoS Computational Biology (4 papers)Biophysical Journal (4 papers)Molecular BioSystems (3 papers)
- Partner nations
- United StatesUnited KingdomFinland
In The Last Decade
Harish Shankaran
41 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 130
- Hematology 227
- Immunology and Allergy 72
- Biophysics 63
- Molecular Biology 576
- Cell Biology 117
Countries citing papers authored by Harish Shankaran
This map shows the geographic impact of Harish Shankaran'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 Harish Shankaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harish Shankaran more than expected).
Fields of papers citing papers by Harish Shankaran
This network shows the impact of papers produced by Harish Shankaran. 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 Harish Shankaran. The network helps show where Harish Shankaran may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Harish Shankaran, 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 | 2022 | 4 | |
| 2 | 2019 | 10 | |
| 3 | 2018 | 12 | |
| 4 | 2014 | 14 | |
| 5 | 2013 | 15 | |
| 6 | 2012 | 12 | |
| 7 | 2012 | 17 | |
| 8 | 2012 | 1 | |
| 9 | 2011 | 32 | |
| 10 | 2010 | 21 | |
| 11 | 2010 | 4 | |
| 12 | 2010 | 30 | |
| 13 | 2010 | 5 | |
| 14 | 2009 | 19 | |
| 15 | 2009 | 29 | |
| 16 | 2008 | 17 | |
| 17 | 2007 | 66 | |
| 18 | 2007 | 73 | |
| 19 | 2006 | 51 | |
| 20 | 2004 | 50 |
About Harish Shankaran
Harish Shankaran is a scholar working on Hematology, Immunology and Allergy and Modeling and Simulation, having authored 41 papers that have together received 1.2k indexed citations. Recurring topics across this work include HER2/EGFR in Cancer Research (8 papers), Monoclonal and Polyclonal Antibodies Research (8 papers), Blood properties and coagulation (7 papers), Platelet Disorders and Treatments (6 papers), Gene Regulatory Network Analysis (6 papers), Glycosylation and Glycoproteins Research (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Hematology (227 citations), Immunology and Allergy (72 citations) and Biophysics (63 citations). Harish Shankaran has collaborated with scholars based in United States, United Kingdom and Finland. Frequent co-authors include Sriram Neelamegham, H Wiley, Haluk Resat, Paschalis Alexandridis, Lee K. Opresko, William Chrisler, Nikki Bollinger, Danielle L. Ippolito, Yi Zhang and Justin Teeguarden. Their work appears in journals such as PLoS Computational Biology, Biophysical Journal, Molecular BioSystems, BMC Systems Biology and Toxicological Sciences.
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.