Mona Singh
- Molecular Biology top 1%
- RNA and protein synthesis mechanisms 27
- Bioinformatics and Genomic Networks 25
- Protein Structure and Dynamics 23
- Genomics and Phylogenetic Studies 18
- Genomics and Chromatin Dynamics 16
- Machine Learning in Bioinformatics 14
- Gene expression and cancer classification 9
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 8
- Virology top 5%
- Genetics top 5%
- Endocrinology top 5%
Mona Singh
122 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Molecular Biology 4.1k
- Computational Theory and Mathematics 653
- Virology 121
- Genetics 592
- Endocrinology 84
Countries citing papers authored by Mona Singh
This map shows the geographic impact of Mona Singh'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 Mona Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mona Singh more than expected).
Fields of papers citing papers by Mona Singh
This network shows the impact of papers produced by Mona Singh. 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 Mona Singh. The network helps show where Mona Singh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mona Singh, 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 | 2024 | 2 | |
| 3 | 2024 | 11 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 5 | |
| 7 | 2021 | 2 | |
| 8 | 2021 | 58 | |
| 9 | 2020 | 30 | |
| 10 | 2018 | 10 | |
| 11 | 2018 | 31 | |
| 12 | 2017 | 4 | |
| 13 | Estimation of heterosis in linseed (Linum usitatissimum L.). | 2014 | 3 |
| 14 | Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine | 2012 | 19 |
| 15 | Molecular marker assisted pyramiding of leaf rust resistance genes Lr19 and Lr28 in bread wheat (Triticum aestivum L.) variety HD2687 | 2011 | 12 |
| 16 | 2011 | 2 | |
| 17 | 2009 | 91 | |
| 18 | 2003 | 238 | |
| 19 | Recovery of desirable mutations in wheat. | 2000 | 3 |
| 20 | Monosomic Analysis in Bread Wheat. III. Identification of Chromosomes Carrying Genes for Resistance to Two Races of Yellow Rust in Cometa Klein | 1959 | 3 |
About Mona Singh
Mona Singh is a scholar working on Molecular Biology, Virology, Aging, Computational Theory and Mathematics and Cancer Research, having authored 126 papers that have together received 5.3k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (27 papers), Bioinformatics and Genomic Networks (25 papers), Protein Structure and Dynamics (23 papers), Genomics and Phylogenetic Studies (18 papers), Genomics and Chromatin Dynamics (16 papers), Machine Learning in Bioinformatics (14 papers), Gene expression and cancer classification (9 papers) and Computational Drug Discovery Methods (8 papers). The work is most often cited by research in Molecular Biology (4.1k citations), Computational Theory and Mathematics (653 citations), Virology (121 citations), Genetics (592 citations) and Endocrinology (84 citations). Mona Singh has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include John A. Capra, Bernard Chazelle, Anton V. Persikov, Peter S. Kim, Peng Jiang, V.N. Malashkevich, Kam Jim, Elena Nabieva, Bonnie Berger and Jimin Song. Their work appears in journals such as Bioinformatics, PLoS Computational Biology, Nucleic Acids Research, Proceedings of the National Academy of Sciences and Genome biology.
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.