Deepak Mav

2.7k citations
39 papers · 2.0k · h-index 19

Impact in

Papers in

    • Epigenetics and DNA Methylation 8
    • Gene expression and cancer classification 7
    • Molecular Biology Techniques and Applications 5
    • Cancer-related gene regulation 3
    • Metabolomics and Mass Spectrometry Studies 3
    • Bioinformatics and Genomic Networks 3

Deepak Mav

36 papers receiving 1.9k citations

Peers

Deepak Mav
Comparison fields: 5 of 142
  • Cancer Research 335
  • Health, Toxicology and Mutagenesis 287
  • Molecular Biology 1.0k
  • Environmental Chemistry 103
  • Oncology 241
Replace Ruchir Shah with:
Ruchir Shah United States
David P. Lovell United Kingdom
Maria Teresa Landi United States
Arpit Tandon United States
Ting Ye China
Jimmie B. Vaught United States
Sylvia E. Escher Germany
John Curtis Seely United States
Amar V. Singh United States
John F. Gierthy United States
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 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012322
2 2018163
3 2010142
4 2011139
5 2016134
6 2018114
7 2008109
8 202094
9 201391
10 201387
11 201083
12 200978
13 201457
14 201856
15 201350
16 200737
17 202236
18 201135
19 201424
20 200815

About Deepak Mav

Deepak Mav is a scholar working on Molecular Biology, Cancer Research, Environmental Chemistry, Health, Toxicology and Mutagenesis and Computational Theory and Mathematics, having authored 39 papers that have together received 2.0k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (8 papers), Gene expression and cancer classification (7 papers), Per- and polyfluoroalkyl substances research (5 papers), Molecular Biology Techniques and Applications (5 papers), Computational Drug Discovery Methods (3 papers), Cancer-related gene regulation (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Bioinformatics and Genomic Networks (3 papers). The work is most often cited by research in Cancer Research (335 citations), Health, Toxicology and Mutagenesis (287 citations), Molecular Biology (1.0k citations), Environmental Chemistry (103 citations) and Oncology (241 citations). Deepak Mav has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Ruchir Shah, Paul A. Wade, Dhiral Phadke, Archana Dhasarathy, B. Alex Merrick, Scott S. Auerbach, Sara A. Grimm, Arpit Tandon, Shawn Harris and Piotr A. Mieczkowski. Their work appears in journals such as PLoS ONE, Bioinformatics and Biology Insights, Toxicological Sciences, Bioinformatics 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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