Debashis Ghosh
Impact in
- Cancer Research top 0.5%
- Cancer-related molecular mechanisms research
- Molecular Biology top 0.5%
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- Cancer-related gene regulation
Papers in
-
- Statistical Methods and Inference 40
- Statistical Methods in Clinical Trials 34
- Advanced Causal Inference Techniques 32
- Statistical Methods and Bayesian Inference 27
- Co-authors
- Arul M. ChinnaiyanTerrence R. BarretteDaniel R. RhodesJianjun YuNandan DeshpandeK. ShankerMargit BurmeisterSrijan Sen
- Journals
- Biometrics (12 papers)Bioinformatics (8 papers)Statistics in Medicine (8 papers)BMC Bioinformatics (7 papers)PLoS ONE (6 papers)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Debashis Ghosh
229 papers receiving 11.0k citations
Hit Papers
Peers
Comparison fields: 5 of 202
- Cancer Research 1.9k
- Molecular Biology 6.3k
- Statistics and Probability 735
- Oncology 1.8k
- Pulmonary and Respiratory Medicine 1.7k
Countries citing papers authored by Debashis Ghosh
This map shows the geographic impact of Debashis Ghosh'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 Debashis Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debashis Ghosh more than expected).
Fields of papers citing papers by Debashis Ghosh
This network shows the impact of papers produced by Debashis Ghosh. 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 Debashis Ghosh. The network helps show where Debashis Ghosh may publish in the future.
Co-authors
The 25 scholars most cited alongside Debashis Ghosh, 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 | 4 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 16 | |
| 5 | 2023 | 5 | |
| 6 | 2022 | 3 | |
| 7 | 2022 | 0 | |
| 8 | 2022 | 4 | |
| 9 | 2022 | 6 | |
| 10 | 2022 | 9 | |
| 11 | 2021 | 32 | |
| 12 | 2020 | 6 | |
| 13 | 2019 | 0 | |
| 14 | 2019 | 34 | |
| 15 | 2018 | 3 | |
| 16 | 2017 | 22 | |
| 17 | Composite endpoint analysis for assessing surrogacy with censored data | 2008 | 1 |
| 18 | 2006 | 18 | |
| 19 | 2004 | 41 | |
| 20 | Effect of solvent pretreatment and selective dye bath additives on physical properties and dyeing behaviour of microdenier polyester fabric | 2003 | 4 |
About Debashis Ghosh
Debashis Ghosh is a scholar working on Statistics and Probability, Health Informatics, Molecular Biology, Biophysics and Management Science and Operations Research, having authored 244 papers that have together received 11.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (43 papers), Statistical Methods and Inference (40 papers), Statistical Methods in Clinical Trials (34 papers), Advanced Causal Inference Techniques (32 papers), Statistical Methods and Bayesian Inference (27 papers), Bioinformatics and Genomic Networks (27 papers), Molecular Biology Techniques and Applications (14 papers) and Genetic Associations and Epidemiology (12 papers). The work is most often cited by research in Cancer Research (1.9k citations), Molecular Biology (6.3k citations), Statistics and Probability (735 citations), Oncology (1.8k citations) and Pulmonary and Respiratory Medicine (1.7k citations). Debashis Ghosh has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Arul M. Chinnaiyan, Terrence R. Barrette, Daniel R. Rhodes, Jianjun Yu, Nandan Deshpande, K. Shanker, Margit Burmeister, Srijan Sen, Shanker Kalyana‐Sundaram and Vasudeva Mahavisno. Their work appears in journals such as Biometrics, Bioinformatics, Statistics in Medicine, BMC Bioinformatics and PLoS ONE.
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.