Debashree Ray

3.2k total citations
30 papers, 476 citations indexed

About

Debashree Ray is a scholar working on Genetics, Modeling and Simulation and Infectious Diseases. According to data from OpenAlex, Debashree Ray has authored 30 papers receiving a total of 476 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Genetics, 8 papers in Modeling and Simulation and 7 papers in Infectious Diseases. Recurrent topics in Debashree Ray's work include Genetic Associations and Epidemiology (14 papers), COVID-19 epidemiological studies (8 papers) and Genetic and phenotypic traits in livestock (8 papers). Debashree Ray is often cited by papers focused on Genetic Associations and Epidemiology (14 papers), COVID-19 epidemiological studies (8 papers) and Genetic and phenotypic traits in livestock (8 papers). Debashree Ray collaborates with scholars based in United States, India and United Kingdom. Debashree Ray's co-authors include Nilanjan Chatterjee, Michael Boehnke, Bhramar Mukherjee, Saonli Basu, Soumik Purkayastha, Maxwell Salvatore, Rupam Bhattacharyya, James S. Pankow, Michael Kleinsasser and Daniel Barker and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Debashree Ray

28 papers receiving 469 citations

Peers

Debashree Ray
Xue Zhong United States
Marta Barreto Portugal
Michael R. Kelly United States
Anna G. C. Boef Netherlands
Raphael Sonabend United Kingdom
Wilson M. Alobuia United States
Andrew Parrish South Africa
Xue Zhong United States
Debashree Ray
Citations per year, relative to Debashree Ray Debashree Ray (= 1×) peers Xue Zhong

Countries citing papers authored by Debashree Ray

Since Specialization
Citations

This map shows the geographic impact of Debashree Ray'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 Debashree Ray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debashree Ray more than expected).

Fields of papers citing papers by Debashree Ray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Debashree Ray. 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 Debashree Ray. The network helps show where Debashree Ray may publish in the future.

Co-authorship network of co-authors of Debashree Ray

This figure shows the co-authorship network connecting the top 25 collaborators of Debashree Ray. A scholar is included among the top collaborators of Debashree Ray 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 Debashree Ray. Debashree Ray 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.
Park, Ji Won & Debashree Ray. (2025). A robust pleiotropy method with applications to lipid traits and to inflammatory bowel disease subtypes with sample overlap. Human Genetics and Genomics Advances. 7(1). 100501–100501.
3.
Qi, Guanghao, Surya B. Chhetri, Debashree Ray, et al.. (2024). Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants. Nature Communications. 15(1). 6985–6985. 3 indexed citations
4.
Ray, Debashree, Stephanie Loomis, Adrienne Tin, et al.. (2024). Characterizing Common and Rare Variations in Nontraditional Glycemic Biomarkers Using Multivariate Approaches on Multiancestry ARIC Study. Diabetes. 73(9). 1537–1550. 2 indexed citations
5.
Wang, Jennifer, Mark Zafereo, Maria E. Cabanillas, et al.. (2024). The Association Between Thyroid Differentiation Score and Survival Outcomes in Papillary Thyroid Carcinoma. The Journal of Clinical Endocrinology & Metabolism. 110(2). 356–363. 7 indexed citations
6.
Datta, Jyotishka, Debashree Ray, Swapnil Mishra, et al.. (2023). Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021. SHILAP Revista de lepidopterología. 3(12). e0002063–e0002063.
7.
Wang, Jennifer, Mark Zafereo, Wenyi Wang, Corinne E. Joshu, & Debashree Ray. (2023). Association of Polygenic Score With Tumor Molecular Subtypes in Papillary Thyroid Carcinoma. The Journal of Clinical Endocrinology & Metabolism. 109(1). e306–e313. 1 indexed citations
8.
Salvatore, Maxwell, Soumik Purkayastha, Rupam Bhattacharyya, et al.. (2022). Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience. Science Advances. 8(24). eabp8621–eabp8621. 15 indexed citations
9.
Meng, Weihua, Parminder Singh Reel, Aravind Lathika Rajendrakumar, et al.. (2022). A Meta-Analysis of the Genome-Wide Association Studies on Two Genetically Correlated Phenotypes Suggests Four New Risk Loci for Headaches. PubMed. 3(1). 64–76. 7 indexed citations
10.
Ray, Debashree, Alvaro Muñoz, Mingyu Zhang, et al.. (2022). Meta-analysis under imbalance in measurement of confounders in cohort studies using only summary-level data. BMC Medical Research Methodology. 22(1). 143–143. 2 indexed citations
11.
Purkayastha, Soumik, et al.. (2021). Estimating the wave 1 and wave 2 infection fatality rates from SARS-CoV-2 in India. BMC Research Notes. 14(1). 262–262. 19 indexed citations
12.
Zhang, Wanying, Jacqueline B. Hetmanski, Elizabeth J. Leslie, et al.. (2021). Detecting Gene-Environment Interaction for Maternal Exposures Using Case-Parent Trios Ascertained Through a Case With Non-Syndromic Orofacial Cleft. Frontiers in Cell and Developmental Biology. 9. 621018–621018. 3 indexed citations
13.
Bhattacharyya, Rupam, et al.. (2021). Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates. Scientific Reports. 11(1). 9748–9748. 12 indexed citations
14.
Ray, Debashree, Wanying Zhang, Elizabeth J. Leslie, et al.. (2021). Pleiotropy method reveals genetic overlap between orofacial clefts at multiple novel loci from GWAS of multi-ethnic trios. PLoS Genetics. 17(7). e1009584–e1009584. 20 indexed citations
15.
Purkayastha, Soumik, Rupam Bhattacharyya, Maxwell Salvatore, et al.. (2021). A comparison of five epidemiological models for transmission of SARS-CoV-2 in India. BMC Infectious Diseases. 21(1). 533–533. 26 indexed citations
16.
Salvatore, Maxwell, Deepankar Basu, Debashree Ray, et al.. (2020). Comprehensive public health evaluation of lockdown as a non-pharmaceutical intervention on COVID-19 spread in India: national trends masking state-level variations. BMJ Open. 10(12). e041778–e041778. 43 indexed citations
17.
Ray, Debashree & Nilanjan Chatterjee. (2020). A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between Type 2 Diabetes and Prostate Cancer. PLoS Genetics. 16(12). e1009218–e1009218. 87 indexed citations
18.
Ray, Debashree, James S. Pankow, & Saonli Basu. (2015). USAT: A Unified Score‐Based Association Test for Multiple Phenotype‐Genotype Analysis. Genetic Epidemiology. 40(1). 20–34. 33 indexed citations
19.
Ray, Debashree, Xiang Li, Wei Pan, James S. Pankow, & Saonli Basu. (2015). A Bayesian Partitioning Model for the Detection of Multilocus Effects in Case-Control Studies. Human Heredity. 79(2). 69–79. 4 indexed citations
20.
Basu, Saonli, Yiwei Zhang, Debashree Ray, et al.. (2013). A Rapid Gene-Based Genome-Wide Association Test with Multivariate Traits. Human Heredity. 76(2). 53–63. 13 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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