Author

Rohan Nidumbur

University of Maryland, College Park

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:GWAS / association mapping· 1 Organism:human· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Anjing LiuiD· 1 shared Chirag M. LakhaniiD· 1 shared David A. KnowlesiD· 1 shared Gao T. WangiD· 1 shared Giacomo CavalcaiD· 1 shared Philip L. De JageriD· 1 shared Ru FengiD· 1 shared Towfique RajiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Anjing LiuORCID

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1 paper

Recent·Most cited

Machine Learning-Based Prediction of Cell-type Resolved Brain eQTLs Enhances Discovery of Variants Explaining Alzheimer's Disease Heritability

Chirag M. Lakhani, Giacomo Cavalca, Anjing Liu, Rohan Nidumbur, Ru Feng, Towfique Raj, Philip L. De Jager, Gao T. Wang, David A. Knowles

The paper develops scEEMS models to predict cell-type-specific eQTLs, enhancing discovery of AD risk variants by linking them to cell-type-specific genes.

medRxiv · Dec 4, 2025 · PreprintGenetic & Genomic Medicine