Deepa Acharya

669 citations
10 papers · 174 · h-index 6

Impact in

Papers in

    • Genomics and Phylogenetic Studies 5
    • Metabolomics and Mass Spectrometry Studies 3
    • Microbial Metabolic Engineering and Bioproduction 2
    • Bioinformatics and Genomic Networks 1
    • Microbial Natural Products and Biosynthesis 5

Deepa Acharya

9 papers receiving 172 citations

Peers

Deepa Acharya
Comparison fields: 5 of 53
  • Pharmacology 50
  • Biotechnology 21
  • Molecular Biology 124
  • Biological Psychiatry 3
  • Food Science 17
Replace Nuo Tian with:
Nuo Tian China
Charles B. Larson United States
Thaïs Hautbergue France
Almut Mentz Germany
Annika Jagels Germany
Víctor H. Tierrafría Mexico
Yongqiang Li China
Don D. Nguyen United States
Librada A. Atencio Panama
Rita Dornetshuber-Fleiss Austria
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Citations per field
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Nuo Tian · 1×
Citations per year

Countries citing papers authored by Deepa Acharya

Since Specialization
Citations

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

Fields of papers citing papers by Deepa Acharya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 202077
2 202153
3 202217
4 201910
5 20245
6 20245
7 20183
8 20252
9 20182
10 20210

About Deepa Acharya

Deepa Acharya is a scholar working on Molecular Biology, Pharmacology, Biotechnology, Computational Theory and Mathematics and Ecological Modeling, having authored 10 papers that have together received 174 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Microbial Natural Products and Biosynthesis (5 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Species Distribution and Climate Change (1 paper), Algal biology and biofuel production (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Pharmacology (50 citations), Biotechnology (21 citations), Molecular Biology (124 citations), Biological Psychiatry (3 citations) and Food Science (17 citations). Deepa Acharya has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include Pieter C. Dorrestein, Asker Brejnrod, Sebastian Böcker, Jo Handelsman, Mingxun Wang, Daniel McDonald, Anupriya Tripathi, Madeleine Ernst, Marcus Ludwig and Qiyun Zhu. Their work appears in journals such as Nature Communications, ACS Chemical Biology, Nature Chemical Biology, Journal of the American Society for Mass Spectrometry and Cell Host & Microbe.

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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