Arpit Tandon

1.4k citations
19 papers · 701 · h-index 15

Impact in

Papers in

    • RNA modifications and cancer 3
    • Genomics and Chromatin Dynamics 2
    • Metabolomics and Mass Spectrometry Studies 2

Arpit Tandon

19 papers receiving 692 citations

Peers

Arpit Tandon
Comparison fields: 5 of 131
  • Health Informatics 23
  • Health, Toxicology and Mutagenesis 147
  • Small Animals 70
  • Statistics, Probability and Uncertainty 56
  • Cancer Research 111
Replace Jason Phillips with:
Jason Phillips United States
Deepak Mav United States
Brian E. Howard United States
Yi‐Hui Zhou United States
Ilona Silins Sweden
Shannon Bell United States
Clemens Wittwehr Italy
Cameron MacKay United Kingdom
Thomas Sheffield United States
Sylvia E. Escher Germany
Arpit Tandon relative to Jason Phillips United States Jason Phillips's profile →
Citations per field
00.5×5.7×
Jason Phillips · 1×
Citations per year

Countries citing papers authored by Arpit Tandon

Since Specialization
Citations

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

Fields of papers citing papers by Arpit Tandon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Arpit Tandon, 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 Arpit Tandon Line = papers co-authored together Arpit Tandon links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2018153
2 2016120
3 202090
4 202045
5 201244
6 201741
7 201131
8 201630
9 201125
10 201722
11 202018
12 201717
13 201417
14 201414
15 201314
16 20229
17 20176
18 20254
19 20251

About Arpit Tandon

Arpit Tandon is a scholar working on Molecular Biology, Oncology, Computational Theory and Mathematics, Cancer Research and Small Animals, having authored 19 papers that have together received 701 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), RNA modifications and cancer (3 papers), MicroRNA in disease regulation (2 papers), Animal testing and alternatives (2 papers), Genomics and Chromatin Dynamics (2 papers), Cancer-related molecular mechanisms research (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers) and Effects and risks of endocrine disrupting chemicals (2 papers). The work is most often cited by research in Health Informatics (23 citations), Health, Toxicology and Mutagenesis (147 citations), Small Animals (70 citations), Statistics, Probability and Uncertainty (56 citations) and Cancer Research (111 citations). Arpit Tandon has collaborated with scholars based in United States, India and Netherlands. Frequent co-authors include Ruchir Shah, Jason Phillips, Deepak Mav, Brian E. Howard, Andrew A. Rooney, B. Alex Merrick, Vickie R. Walker, Kristina A. Thayer, Siddharth Sinha and Cristian Coarfa. Their work appears in journals such as BMC Bioinformatics, SLAS DISCOVERY, Bioinformatics, Structure and Toxicology in Vitro.

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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