Venkatesh Muthukrishnan
- Molecular Biology top 10%
- Computational Theory and Mathematics top 2%
- Artificial Intelligence top 10%
- Spectroscopy top 10%
- Pharmacology top 10%
- Co-authors
- Adriano DekkerChristoph SteinbeckJanna HastingsGareth OwenNamrata KaleSteve TurnerMarcus EnnisPedro Mendes
- Topics
- Biomedical Text Mining and Ontologies (4 papers)Microbial Metabolic Engineering and Bioproduction (4 papers)Metabolomics and Mass Spectrometry Studies (3 papers)
- Journals
- Nucleic Acids ResearchSHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- United KingdomSwitzerlandIndia
In The Last Decade
Venkatesh Muthukrishnan
12 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Molecular Biology 982
- Computational Theory and Mathematics 303
- Artificial Intelligence 179
- Spectroscopy 98
- Pharmacology 92
Countries citing papers authored by Venkatesh Muthukrishnan
This map shows the geographic impact of Venkatesh Muthukrishnan'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 Venkatesh Muthukrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Venkatesh Muthukrishnan more than expected).
Fields of papers citing papers by Venkatesh Muthukrishnan
This network shows the impact of papers produced by Venkatesh Muthukrishnan. 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 Venkatesh Muthukrishnan. The network helps show where Venkatesh Muthukrishnan may publish in the future.
Co-authorship network of co-authors of Venkatesh Muthukrishnan
This figure shows the co-authorship network connecting the top 25 collaborators of Venkatesh Muthukrishnan. A scholar is included among the top collaborators of Venkatesh Muthukrishnan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Venkatesh Muthukrishnan. Venkatesh Muthukrishnan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 126 | |
| 3 | 6 | |
| 4 | 1 | |
| 5 | 14 | |
| 6 | 3 | |
| 7 | ChEBI in 2016: Improved services and an expanding collection of metabolitesbreakdown → | 648 |
| 8 | 31 | |
| 9 | 8 | |
| 10 | Modular Extensions to the ChEBI Ontology. | 2 |
| 11 | The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013breakdown → | 419 |
| 12 | 5 |
About Venkatesh Muthukrishnan
Venkatesh Muthukrishnan is a scholar working on Neuropsychology and Physiological Psychology, Computational Theory and Mathematics and Psychiatry and Mental health, having authored 12 papers that have together received 1.3k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Microbial Metabolic Engineering and Bioproduction (4 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Computational Theory and Mathematics (303 citations), Molecular Biology (982 citations) and Information Systems and Management (49 citations). Venkatesh Muthukrishnan has collaborated with scholars based in United Kingdom, Switzerland and India. Frequent co-authors include Adriano Dekker, Christoph Steinbeck, Janna Hastings, Gareth Owen, Namrata Kale, Steve Turner, Marcus Ennis, Pedro Mendes, Neil Swainston and Bhavana Harsha. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.
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.