Sunjay Sethi

1.3k citations
30 papers · 856 indexed · h-index 19

Impact in

Papers in

Sunjay Sethi

30 papers receiving 836 citations

Peers

Sunjay Sethi
Comparison fields: 5 of 109
  • Health, Toxicology and Mutagenesis 285
  • Biological Psychiatry 31
  • Developmental Neuroscience 49
  • Cellular and Molecular Neuroscience 128
  • Computer Vision and Pattern Recognition 130
Replace Andrea Diana with:
Andrea Diana Italy
Abhay Sharma India
Susanne Gerber Germany
Shinichiro Matsumoto Japan
Didima M.G. de Groot Netherlands
Shanker Swaminathan United States
Arpan Kumar Maiti India
J. Todd Auman United States
Xiaofeng Zhang China
Susan V. Smith United States
Sunjay Sethi relative to Andrea Diana Italy Andrea Diana's profile →
Citations per field
00.5×10×15×18.6×
Andrea Diana · 1×
Citations per year

Countries citing papers authored by Sunjay Sethi

Since Specialization
Citations

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

Fields of papers citing papers by Sunjay Sethi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sunjay Sethi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sunjay Sethi Line = papers co-authored together Sunjay Sethi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002138
2 201667
3 201965
4 201954
5 201950
6 201749
7 201746
8 201745
9 201834
10 201824
11 202124
12 201924
13 201722
14 201622
15 201721
16 201919
17 202219
18 201818
19 201818
20 202017

About Sunjay Sethi

Sunjay Sethi is a scholar working on Developmental Neuroscience, Health, Toxicology and Mutagenesis, Cellular and Molecular Neuroscience, Biological Psychiatry and Small Animals, having authored 30 papers that have together received 856 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (9 papers), Toxic Organic Pollutants Impact (8 papers), Effects and risks of endocrine disrupting chemicals (6 papers), Genetics and Neurodevelopmental Disorders (4 papers), Anesthesia and Neurotoxicity Research (3 papers), Computational Drug Discovery Methods (2 papers), Prenatal Substance Exposure Effects (2 papers) and Animal testing and alternatives (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (285 citations), Biological Psychiatry (31 citations), Developmental Neuroscience (49 citations), Cellular and Molecular Neuroscience (128 citations) and Computer Vision and Pattern Recognition (130 citations). Sunjay Sethi has collaborated with scholars based in United States, Vietnam and Sweden. Frequent co-authors include Pamela J. Lein, Kimberly P. Keil, Marco La Cascia, Stan Sclaroff, Machelle Wilson, Birgit Puschner, Carolyn Klocke, Isaac N. Pessah, Yanping Lin and Hans‐Joachim Lehmler. Their work appears in journals such as Frontiers in Neuroscience, Environmental Science & Technology, Toxicological Sciences, Archives of Toxicology and Toxics.

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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