Shankar Venkatraman

2.9k citations
22 papers · 2.0k indexed · 1 hit paper · h-index 11
Topics
Computational Drug Discovery Methods (4 papers)Cholinesterase and Neurodegenerative Diseases (3 papers)Peptidase Inhibition and Analysis (3 papers)

In The Last Decade

Shankar Venkatraman

22 papers receiving 1.9k citations

Hit Papers

The cGAS–STING pathway as a therapeutic target in inflamm...202120262022202420214008001.2k

Peers

Shankar Venkatraman
Comparison fields: 5 of 99
  • Molecular Biology 1.1k
  • Immunology 995
  • Infectious Diseases 302
  • Oncology 208
  • Cancer Research 192
Replace Terence G. Porter with:
Terence G. Porter United States
Maho Niwa United States
Xuhong Cheng United States
Yuehan Feng Switzerland
Robert W. Marquis United States
Chunqing Guo United States
Maximilien Tailler France
Jason D. Katz United States
Gabriella Miklóssy United States
Eva Prchalová United States
Shankar Venkatraman relative to Terence G. Porter United States Terence G. Porter's profile →
Citations per field
00.5×20×40×60×80.6×
Terence G. Porter · 1×
Citations per year

Countries citing papers authored by Shankar Venkatraman

Since Specialization
Citations

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

Fields of papers citing papers by Shankar Venkatraman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shankar Venkatraman

This figure shows the co-authorship network connecting the top 25 collaborators of Shankar Venkatraman. A scholar is included among the top collaborators of Shankar Venkatraman 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 Shankar Venkatraman. Shankar Venkatraman 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
#WorkIndexed citations
1
The cGAS–STING pathway as a therapeutic target in inflammatory diseasesbreakdown →
1401
2 2
3 111
4 1
5 6
6 73
7 63
8 8
9 6
10 10
11 29
12 45
13 13
14 66
15 7
16 3
17 10
18 44
19 46
20 12

About Shankar Venkatraman

Shankar Venkatraman is a scholar working on Biological Psychiatry, Biochemistry and Computational Theory and Mathematics, having authored 22 papers that have together received 2.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Cholinesterase and Neurodegenerative Diseases (3 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Immunology (995 citations), Biological Psychiatry (65 citations) and Biochemistry (120 citations). Shankar Venkatraman has collaborated with scholars based in United States, Canada and Switzerland. Frequent co-authors include Jason D. Katz, Andrea Ablasser, Alexiane Decout, Lawrence W. Dillard, Jing Yuan, Brian M. McKeever, Ya‐Jun Zheng, Suresh B. Singh, Rodney L. Johnson and Gregg Wesolowski. Their work appears in journals such as Nature reviews. Immunology, Analytical Biochemistry and Journal of Medicinal Chemistry.

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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