Krishnadev Oruganty
- Molecular Biology top 10%
- Protein Structure and Dynamics 8
- Genomics and Phylogenetic Studies 5
- Bioinformatics and Genomic Networks 4
- Machine Learning in Bioinformatics 3
- Protein Kinase Regulation and GTPase Signaling 3
- RNA and protein synthesis mechanisms 3
- Cell Biology top 10%
- Microtubule and mitosis dynamics 3
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- Enzyme Structure and Function 6
- Co-authors
- Natarajan KannanNarayanaswamy SrinivasanHiruy S. MeharenaSusan S. TaylorAishwarya NeneAlexandr P. KornevMalik M. KeshwaniPhilip Chang
- Journals
- Nature (1 paper)Proceedings of the National Academy of Sciences (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Krishnadev Oruganty
22 papers receiving 782 citations
Peers
Comparison fields: 5 of 87
- Molecular Biology 698
- Cell Biology 132
- Computational Theory and Mathematics 117
- Biochemistry 26
- Genetics 30
Countries citing papers authored by Krishnadev Oruganty
This map shows the geographic impact of Krishnadev Oruganty'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 Krishnadev Oruganty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Krishnadev Oruganty more than expected).
Fields of papers citing papers by Krishnadev Oruganty
This network shows the impact of papers produced by Krishnadev Oruganty. 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 Krishnadev Oruganty. The network helps show where Krishnadev Oruganty may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Krishnadev Oruganty, 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 | 2020 | 9 | |
| 2 | 2018 | 99 | |
| 3 | 2016 | 17 | |
| 4 | 2016 | 31 | |
| 5 | 2015 | 30 | |
| 6 | 2015 | 60 | |
| 7 | 2015 | 20 | |
| 8 | 2014 | 89 | |
| 9 | 2013 | 169 | |
| 10 | 2013 | 8 | |
| 11 | 2012 | 31 | |
| 12 | 2011 | 40 | |
| 13 | 2011 | 11 | |
| 14 | 2009 | 25 | |
| 15 | 2009 | 6 | |
| 16 | 2008 | 27 | |
| 17 | 2007 | 11 | |
| 18 | 2005 | 17 | |
| 19 | 2005 | 73 | |
| 20 | 2005 | 9 |
About Krishnadev Oruganty
Krishnadev Oruganty is a scholar working on Cell Biology, Molecular Biology and Biochemistry, having authored 22 papers that have together received 823 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Enzyme Structure and Function (6 papers), Genomics and Phylogenetic Studies (5 papers), Bioinformatics and Genomic Networks (4 papers), Machine Learning in Bioinformatics (3 papers), Microtubule and mitosis dynamics (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Molecular Biology (698 citations), Cell Biology (132 citations) and Computational Theory and Mathematics (117 citations). Krishnadev Oruganty has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Natarajan Kannan, Narayanaswamy Srinivasan, Hiruy S. Meharena, Susan S. Taylor, Aishwarya Nene, Alexandr P. Kornev, Malik M. Keshwani, Philip Chang, Zachary A. Wood and Subhajyoti De. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids 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.