Soma Barman
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Organic Chemistry
- Cardiology and Cardiovascular Medicine
- Oncology
- Co-authors
- Sanat K. MandalMeenal MoudgilJames DavieAntara GhoshTanya ParishJaydeb BhaumikMarek ŁośSoumya Panigrahi
- Topics
- Machine Learning in Bioinformatics (20 papers)Fractal and DNA sequence analysis (20 papers)RNA and protein synthesis mechanisms (13 papers)
- Cited by
- Computational Theory and MathematicsMolecular BiologyCardiology and Cardiovascular Medicine
- Partner nations
- IndiaCanadaUnited States
In The Last Decade
Soma Barman
49 papers receiving 751 citations
Peers
Comparison fields: 5 of 125
- Molecular Biology 412
- Computational Theory and Mathematics 109
- Organic Chemistry 84
- Cardiology and Cardiovascular Medicine 77
- Oncology 71
Countries citing papers authored by Soma Barman
This map shows the geographic impact of Soma Barman'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 Soma Barman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soma Barman more than expected).
Fields of papers citing papers by Soma Barman
This network shows the impact of papers produced by Soma Barman. 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 Soma Barman. The network helps show where Soma Barman may publish in the future.
Co-authorship network of co-authors of Soma Barman
This figure shows the co-authorship network connecting the top 25 collaborators of Soma Barman. A scholar is included among the top collaborators of Soma Barman 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 Soma Barman. Soma Barman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 35 | |
| 8 | 32 | |
| 9 | CA-based area optimized three bytes error detecting codes | 2 |
| 10 | 12 | |
| 11 | 9 | |
| 12 | 13 | |
| 13 | 15 | |
| 14 | Identification and analysis of coding and non-coding regions of a DNA sequence by positional frequency distribution of nucleotides (PFDN) algorithm | 16 |
| 15 | 200 | |
| 16 | 15 | |
| 17 | 25 | |
| 18 | Genetic divergence and interrelationship analysis in grain amaranth (Amaranthus hypochondriacus) germplasm | 8 |
| 19 | 3 | |
| 20 | In vitro pollen germination in Morus indica L. | 1 |
About Soma Barman
Soma Barman is a scholar working on Otorhinolaryngology, Molecular Biology and Hardware and Architecture, having authored 57 papers that have together received 771 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (20 papers), Fractal and DNA sequence analysis (20 papers) and RNA and protein synthesis mechanisms (13 papers). The work is most often cited by research in Computational Theory and Mathematics (109 citations), Molecular Biology (412 citations) and Cardiology and Cardiovascular Medicine (77 citations). Soma Barman has collaborated with scholars based in India, Canada and United States. Frequent co-authors include Sanat K. Mandal, Meenal Moudgil, James Davie, Antara Ghosh, Tanya Parish, Jaydeb Bhaumik, Marek Łoś, Soumya Panigrahi, Jörg Stetefeld and Jaganmohan R. Jangamreddy. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and Antimicrobial Agents and Chemotherapy.
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.