Debashis Ghosh

2.0k total citations
47 papers, 1.4k citations indexed

About

Debashis Ghosh is a scholar working on Molecular Biology, Genetics and Statistics and Probability. According to data from OpenAlex, Debashis Ghosh has authored 47 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 13 papers in Genetics and 12 papers in Statistics and Probability. Recurrent topics in Debashis Ghosh's work include Gene expression and cancer classification (21 papers), Statistical Methods in Clinical Trials (8 papers) and Molecular Biology Techniques and Applications (8 papers). Debashis Ghosh is often cited by papers focused on Gene expression and cancer classification (21 papers), Statistical Methods in Clinical Trials (8 papers) and Molecular Biology Techniques and Applications (8 papers). Debashis Ghosh collaborates with scholars based in United States, Puerto Rico and Germany. Debashis Ghosh's co-authors include George C. Tseng, Eleanor Feingold, Hyungwon Choi, Alexey I. Nesvizhskii, Dawei Liu, Xihong Lin, Laila Poisson, Arul M. Chinnaiyan, Zhaohui Qin and Ronglai Shen and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and NeuroImage.

In The Last Decade

Debashis Ghosh

45 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Debashis Ghosh United States 17 825 339 156 122 111 47 1.4k
Hae‐Won Uh Netherlands 27 923 1.1× 240 0.7× 398 2.6× 63 0.5× 101 0.9× 64 2.0k
Anat Reiner‐Benaim Israel 15 993 1.2× 206 0.6× 202 1.3× 195 1.6× 30 0.3× 45 2.1k
Alan R. Dabney United States 21 1.0k 1.2× 111 0.3× 63 0.4× 88 0.7× 389 3.5× 37 1.6k
Peter Groenen Switzerland 21 864 1.0× 503 1.5× 253 1.6× 59 0.5× 13 0.1× 45 2.0k
Grzegorz A. Rempała United States 22 735 0.9× 234 0.7× 524 3.4× 120 1.0× 9 0.1× 108 1.9k
Rashmi Gopal-Srivastava United States 17 704 0.9× 267 0.8× 35 0.2× 45 0.4× 61 0.5× 30 1.1k
Bill Pikounis United States 11 337 0.4× 93 0.3× 138 0.9× 39 0.3× 12 0.1× 16 802
Abhay Jere India 12 731 0.9× 162 0.5× 56 0.4× 177 1.5× 38 0.3× 18 1.3k
David Engler United States 27 938 1.1× 161 0.5× 194 1.2× 200 1.6× 16 0.1× 68 1.9k
Claudia Rangel‐Escareño Mexico 20 642 0.8× 123 0.4× 208 1.3× 143 1.2× 8 0.1× 68 1.4k

Countries citing papers authored by Debashis Ghosh

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Debashis Ghosh

This figure shows the co-authorship network connecting the top 25 collaborators of Debashis Ghosh. A scholar is included among the top collaborators of Debashis Ghosh 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 Debashis Ghosh. Debashis Ghosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ghosh, Debashis, et al.. (2014). MRHMMs: Multivariate Regression Hidden Markov Models and the variantS. Bioinformatics. 30(12). 1755–1756. 2 indexed citations
2.
Li, Yihan & Debashis Ghosh. (2014). Meta-analysis based on weighted ordered P-values for genomic data with heterogeneity. BMC Bioinformatics. 15(1). 226–226. 12 indexed citations
3.
Bekker, Charissa de, et al.. (2014). Species-specific ant brain manipulation by a specialized fungal parasite. BMC Evolutionary Biology. 14(1). 166–166. 80 indexed citations
4.
Ghosh, Debashis, et al.. (2013). Association testing to detect gene–gene interactions on sex chromosomes in trio data. Frontiers in Genetics. 4. 239–239. 3 indexed citations
5.
Tseng, George C., Debashis Ghosh, & Eleanor Feingold. (2012). Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Research. 40(9). 3785–3799. 376 indexed citations
6.
Chen, Fang, Xicheng Ding, Ying Ding, et al.. (2011). Proinflammatory Caspase-2-Mediated Macrophage Cell Death Induced by a Rough Attenuated Brucella suis Strain. Infection and Immunity. 79(6). 2460–2469. 40 indexed citations
7.
Ghosh, Debashis. (2010). Detecting outlier genes from high-dimensional data: a fuzzy approach. International Conference on Bioinformatics. 2 indexed citations
8.
Ghosh, Debashis. (2010). Discrete Nonparametric Algorithms for Outlier Detection with Genomic Data. Journal of Biopharmaceutical Statistics. 20(2). 193–208. 15 indexed citations
9.
Ghosh, Debashis & Zhaohui Qin. (2010). Statistical Issues in the Analysis of ChIP-Seq and RNA-Seq Data. Genes. 1(2). 317–334. 11 indexed citations
10.
Chen, Wei, Debashis Ghosh, Trivellore E. Raghunathan, & Daniel J. Sargent. (2009). Bayesian Variable Selection with Joint Modeling of Categorical and Survival Outcomes: An Application to Individualizing Chemotherapy Treatment in Advanced Colorectal Cancer. Biometrics. 65(4). 1030–1040. 12 indexed citations
11.
Chin, Jonathan W., et al.. (2009). Transcriptional effects of CRP* expression in Escherichia coli. Journal of Biological Engineering. 3(1). 13–13. 51 indexed citations
12.
Guðjónsson, Jóhann E., Jun Ding, Xing Li, et al.. (2009). Global Gene Expression Analysis Reveals Evidence for Decreased Lipid Biosynthesis and Increased Innate Immunity in Uninvolved Psoriatic Skin. Journal of Investigative Dermatology. 129(12). 2795–2804. 140 indexed citations
13.
Ghosh, Debashis & Ratna Chakrabarti. (2009). Joint Variable Selection and Classification with Immunohistochemical Data. Biomarker Insights. 4. BMI.S2465–BMI.S2465. 1 indexed citations
14.
Patwa, Tasneem H., Chen Li, Laila Poisson, et al.. (2009). The identification of phosphoglycerate kinase‐1 and histone H4 autoantibodies in pancreatic cancer patient serum using a natural protein microarray. Electrophoresis. 30(12). 2215–2226. 32 indexed citations
15.
Ghosh, Debashis. (2008). On the Plackett Distribution with Bivariate Censored Data. The International Journal of Biostatistics. 4(1). Article 7–Article 7. 2 indexed citations
16.
Haan, Mary N., et al.. (2008). Fasting total homocysteine (tHcy) concentration and mortality in older Mexican Americans. The journal of nutrition health & aging. 12(10). 685–689. 5 indexed citations
17.
Colón‐López, Vivian, Mary N. Haan, Allison E. Aiello, & Debashis Ghosh. (2008). The Effect of Age at Migration on Cardiovascular Mortality Among Elderly Mexican Immigrants. Annals of Epidemiology. 19(1). 8–14. 35 indexed citations
18.
Ghosh, Debashis & Laila Poisson. (2008). “Omics” data and levels of evidence for biomarker discovery. Genomics. 93(1). 13–16. 60 indexed citations
19.
Ghosh, Debashis, Moulinath Banerjee, & Pinaki Biswas. (2008). Inference for Constrained Estimation of Tumor Size Distributions. Biometrics. 64(4). 1009–1017. 4 indexed citations
20.
Ghosh, Debashis & Arul M. Chinnaiyan. (2008). Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation. Biostatistics. 10(1). 60–69. 27 indexed citations

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.

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