Deepak Mav

2.6k citations
35 papers · 1.8k · h-index 18

Impact in

Papers in

    • Epigenetics and DNA Methylation 8
    • Gene expression and cancer classification 7
    • Molecular Biology Techniques and Applications 6
    • Metabolomics and Mass Spectrometry Studies 4
    • Genomics and Phylogenetic Studies 3
    • RNA modifications and cancer 3
    • Cancer-related gene regulation 3

Deepak Mav

33 papers receiving 1.8k citations

Peers

Deepak Mav
Comparison fields: 5 of 145
  • Cancer Research 358
  • Health, Toxicology and Mutagenesis 278
  • Health Informatics 22
  • Molecular Biology 1.1k
  • Oncology 260
Replace Ruchir Shah with:
Ruchir Shah United States
Gregg E. Dinse United States
David P. Lovell United Kingdom
Arpit Tandon United States
Maria Teresa Landi United States
Ting Ye China
Haiyun Wang China
Riccardo Puntoni Italy
Robert R. Delongchamp United States
María Jesús Álvarez-Cubero Spain
Deepak Mav relative to Ruchir Shah United States Ruchir Shah's profile →
Citations per field
00.5×1.5×
Ruchir Shah · 1×
Citations per year

Countries citing papers authored by Deepak Mav

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Mav

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012314
2 2018153
3 2010139
4 2011134
5 2016120
6 2008105
7 2018105
8 202090
9 201385
10 201384
11 201078
12 200967
13 201455
14 201852
15 201347
16 202233
17 201133
18 201423
19 200815
20 201314

About Deepak Mav

Deepak Mav is a scholar working on Molecular Biology, Cancer Research, Oncology, Rheumatology and Computational Theory and Mathematics, having authored 35 papers that have together received 1.8k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (8 papers), Gene expression and cancer classification (7 papers), Molecular Biology Techniques and Applications (6 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Genomics and Phylogenetic Studies (3 papers), Per- and polyfluoroalkyl substances research (3 papers), RNA modifications and cancer (3 papers) and Cancer-related gene regulation (3 papers). The work is most often cited by research in Cancer Research (358 citations), Health, Toxicology and Mutagenesis (278 citations), Health Informatics (22 citations), Molecular Biology (1.1k citations) and Oncology (260 citations). Deepak Mav has collaborated with scholars based in United States, Netherlands and India. Frequent co-authors include Ruchir Shah, Paul A. Wade, Dhiral Phadke, Archana Dhasarathy, B. Alex Merrick, Scott S. Auerbach, Sara A. Grimm, Arpit Tandon, Steven A. Roberts and Joan F. Sterling. Their work appears in journals such as PLoS ONE, Bioinformatics and Biology Insights, Cell Metabolism, Scientific Reports and American Journal of Industrial Medicine.

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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