Arjun Krishnan
- Plant Science top 1%
- Plant Stress Responses and Tolerance 5
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks 22
- Gene expression and cancer classification 19
- Biomedical Text Mining and Ontologies 6
- Machine Learning in Bioinformatics 4
- Molecular Biology Techniques and Applications 4
- Photosynthetic Processes and Mechanisms 4
- Gene Regulatory Network Analysis 3
- Genetics top 5%
- Agronomy and Crop Science top 5%
- Aging top 10%
- Co-authors
- Andy PereiraMadana M.R. AmbavaramAmal HarbOlga G. TroyanskayaAaron K. WongRan ZhangKurniawan Rudi TrijatmikoUtlwang Batlang
- Partner nations
- United StatesIndiaNorway
In The Last Decade
Arjun Krishnan
45 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Plant Science 1.7k
- Molecular Biology 1.8k
- Genetics 531
- Agronomy and Crop Science 115
- Aging 19
Countries citing papers authored by Arjun Krishnan
This map shows the geographic impact of Arjun Krishnan'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 Arjun Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arjun Krishnan more than expected).
Fields of papers citing papers by Arjun Krishnan
This network shows the impact of papers produced by Arjun Krishnan. 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 Arjun Krishnan. The network helps show where Arjun Krishnan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arjun Krishnan, 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 | 2025 | 0 | |
| 2 | 2023 | 13 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 58 | |
| 6 | 2021 | 25 | |
| 7 | 2021 | 13 | |
| 8 | 2020 | 6 | |
| 9 | 2020 | 22 | |
| 10 | 2019 | 19 | |
| 11 | 2017 | 18 | |
| 12 | 2016 | 265 | |
| 13 | 2015 | 19 | |
| 14 | 2015 | 46 | |
| 15 | 2015 | 110 | |
| 16 | Understanding multicellular function and disease with human tissue-specific networksbreakdown → | 2015 | 562 |
| 17 | Drought responsive genes and their functional terms identified by GS FLX Pyro sequencing in maize. | 2014 | 2 |
| 18 | 2012 | 8 | |
| 19 | 2010 | 60 | |
| 20 | 2008 | 15 |
About Arjun Krishnan
Arjun Krishnan is a scholar working on Aging, Molecular Biology, Plant Science, Toxicology and Genetics, having authored 47 papers that have together received 3.3k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (22 papers), Gene expression and cancer classification (19 papers), Biomedical Text Mining and Ontologies (6 papers), Plant Stress Responses and Tolerance (5 papers), Machine Learning in Bioinformatics (4 papers), Molecular Biology Techniques and Applications (4 papers), Photosynthetic Processes and Mechanisms (4 papers) and Gene Regulatory Network Analysis (3 papers). The work is most often cited by research in Plant Science (1.7k citations), Molecular Biology (1.8k citations), Genetics (531 citations), Agronomy and Crop Science (115 citations) and Aging (19 citations). Arjun Krishnan has collaborated with scholars based in United States, India and Norway. Frequent co-authors include Andy Pereira, Madana M.R. Ambavaram, Amal Harb, Olga G. Troyanskaya, Aaron K. Wong, Ran Zhang, Kurniawan Rudi Trijatmiko, Utlwang Batlang, Supratim Basu and Venkategowda Ramegowda. Their work appears in journals such as Bioinformatics, PLANT PHYSIOLOGY, Nucleic Acids Research, Nature Communications and Nature Methods.
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.