Aditya Barve
Impact in
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- Microbial Metabolic Engineering and Bioproduction
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Epigenetics and DNA Methylation
- Protein Structure and Dynamics
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- Microbial Community Ecology and Physiology
Papers in
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- Microbial Metabolic Engineering and Bioproduction 6
- Bioinformatics and Genomic Networks 4
- Protein Structure and Dynamics 4
- Gene Regulatory Network Analysis 3
- Single-cell and spatial transcriptomics 1
- Protein Degradation and Inhibitors 1
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- Acute Myeloid Leukemia Research 2
- Co-authors
- Andreas Wagner (6 shared papers)Evandro Ferrada (1 shared paper)Niv Sabath (1 shared paper)João F. Matias Rodrigues (1 shared paper)Levi J. Beverly (4 shared papers)Lavona Casson (3 shared papers)Mark Wunderlich (2 shared papers)Anna Lyubimova (1 shared paper)
- Journals
- Scientific Reports (1 paper)PLoS Computational Biology (1 paper)BMC Systems Biology (1 paper)Genome Biology and Evolution (1 paper)Cell Research (1 paper)
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Aditya Barve
13 papers receiving 443 citations
Peers
Comparison fields: 5 of 105
- Molecular Biology 325
- Ecology 100
- Genetics 84
- Hematology 29
- Cancer Research 31
Countries citing papers authored by Aditya Barve
This map shows the geographic impact of Aditya Barve'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 Aditya Barve with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Barve more than expected).
Fields of papers citing papers by Aditya Barve
This network shows the impact of papers produced by Aditya Barve. 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 Aditya Barve. The network helps show where Aditya Barve may publish in the future.
Co-authors
The 25 scholars most cited alongside Aditya Barve, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 124 | |
| 2 | 2013 | 107 | |
| 3 | 2019 | 40 | |
| 4 | 2012 | 40 | |
| 5 | 2008 | 35 | |
| 6 | 2019 | 23 | |
| 7 | 2018 | 22 | |
| 8 | 2019 | 17 | |
| 9 | 2015 | 11 | |
| 10 | 2010 | 10 | |
| 11 | 2014 | 9 | |
| 12 | 2018 | 6 | |
| 13 | 2014 | 4 |
About Aditya Barve
Aditya Barve is a scholar working on Molecular Biology, Hematology, Genetics, Genetics and Oncology, having authored 13 papers that have together received 448 indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (6 papers), Bioinformatics and Genomic Networks (4 papers), Protein Structure and Dynamics (4 papers), Gene Regulatory Network Analysis (3 papers), Acute Myeloid Leukemia Research (2 papers), Single-cell and spatial transcriptomics (1 paper), Protein Degradation and Inhibitors (1 paper) and Mesenchymal stem cell research (1 paper). The work is most often cited by research in Molecular Biology (325 citations), Ecology (100 citations), Genetics (84 citations), Hematology (29 citations) and Cancer Research (31 citations). Aditya Barve has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Andreas Wagner, Evandro Ferrada, Niv Sabath, João F. Matias Rodrigues, Levi J. Beverly, Lavona Casson, Mark Wunderlich, Anna Lyubimova, Reinier van der Linden and Chloé S. Baron. Their work appears in journals such as Scientific Reports, PLoS Computational Biology, BMC Systems Biology, Genome Biology and Evolution and Cell Research.
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.