Sushmita Paul
Impact in
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- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
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- Immune cells in cancer
Papers in
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- Gene expression and cancer classification 8
- Bioinformatics and Genomic Networks 7
- Machine Learning in Bioinformatics 6
- Circular RNAs in diseases 3
- RNA Research and Splicing 2
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- MicroRNA in disease regulation 10
- Cancer-related molecular mechanisms research 8
- Co-authors
- Pradipta Maji (8 shared papers)Julio Vera (6 shared papers)Madhumita Madhumita (7 shared papers)Jutta Jordan (1 shared paper)Stephen Reid (1 shared paper)Aline Bözec (1 shared paper)Tobias Bäuerle (1 shared paper)Sophia Sonnewald (1 shared paper)
In The Last Decade
Sushmita Paul
24 papers receiving 366 citations
Peers
Comparison fields: 5 of 84
- Cancer Research 80
- Immunology 68
- Molecular Biology 222
- Computational Theory and Mathematics 38
- Oncology 38
Countries citing papers authored by Sushmita Paul
This map shows the geographic impact of Sushmita Paul'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 Sushmita Paul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sushmita Paul more than expected).
Fields of papers citing papers by Sushmita Paul
This network shows the impact of papers produced by Sushmita Paul. 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 Sushmita Paul. The network helps show where Sushmita Paul may publish in the future.
Co-authors
The 25 scholars most cited alongside Sushmita Paul, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 75 | |
| 2 | 2020 | 64 | |
| 3 | 2019 | 39 | |
| 4 | 2016 | 24 | |
| 5 | 2022 | 20 | |
| 6 | 2014 | 17 | |
| 7 | 2016 | 16 | |
| 8 | 2011 | 13 | |
| 9 | 2020 | 11 | |
| 10 | 2022 | 11 | |
| 11 | 2017 | 10 | |
| 12 | 2014 | 9 | |
| 13 | 2013 | 8 | |
| 14 | 2019 | 7 | |
| 15 | 2015 | 7 | |
| 16 | 2017 | 7 | |
| 17 | 2014 | 7 | |
| 18 | 2019 | 6 | |
| 19 | 2019 | 6 | |
| 20 | 2012 | 5 |
About Sushmita Paul
Sushmita Paul is a scholar working on Molecular Biology, Cancer Research, Pharmacology, Oncology and Computational Theory and Mathematics, having authored 27 papers that have together received 371 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (10 papers), Gene expression and cancer classification (8 papers), Cancer-related molecular mechanisms research (8 papers), Bioinformatics and Genomic Networks (7 papers), Machine Learning in Bioinformatics (6 papers), Circular RNAs in diseases (3 papers), Computational Drug Discovery Methods (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Cancer Research (80 citations), Immunology (68 citations), Molecular Biology (222 citations), Computational Theory and Mathematics (38 citations) and Oncology (38 citations). Sushmita Paul has collaborated with scholars based in India, Germany and Bulgaria. Frequent co-authors include Pradipta Maji, Julio Vera, Madhumita Madhumita, Jutta Jordan, Stephen Reid, Aline Bözec, Tobias Bäuerle, Sophia Sonnewald, Georg Schett and Nicole Hannemann. Their work appears in journals such as Scientific Reports, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Molecular BioSystems, The Journal of Immunology and Journal of Biomedical Informatics.
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.