Author

Javad Rahimikollu

University of PittsburghORCID 0000-0001-5247-5241Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Systems Biology· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:mouse· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Alok V. JoglekariD· 2 shared AnnaElaine RosengartiD· 2 shared Jishnu DasiD· 2 shared Aaron B.I. RoseniD· 1 shared Akash PateliD· 1 shared Alisa A. OmelchenkoiD· 1 shared Amanda C. PoholekiD· 1 shared David Ryan KoesiD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersSystems Biology

Alok V. JoglekarORCID

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3 papers

Recent·Most cited

Systems BiologyNature MethodsPeer-reviewedJul 28, 2025

Sliding Window INteraction Grammar (SWING): a generalized interaction language model for peptide and protein interactions

Jane C Siwek, Alisa A. Omelchenko, Prabal Chhibbar…·Jishnu Das

SWING is a novel interaction language model that predicts peptide:MHC interactions and protein-protein interaction disruptions using sequence data.

27 citationstop 1%

mouseprotein sequence

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Systems BiologyNature MethodsPeer-reviewedFeb 19, 2024

SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains

Javad Rahimikollu, Hanxi Xiao, AnnaElaine Rosengart…·Jishnu Das

SLIDE identifies significant interacting latent factors in multi-omic datasets, revealing biological insights in systemic sclerosis, spatial transcriptomics, and T1D models.

33 citationstop 4%

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GenomicsBioinformaticsPeer-reviewedAug 18, 2020

DataRemix: a universal data transformation for optimal inference from gene expression datasets

Weiguang Mao, Javad Rahimikollu, Ryan M. Hausler, Maria D. Chikina

DataRemix is a normalization method that enhances biological signal detection in gene expression data by tuning hidden factors, outperforming existing methods without external knowledge.

4 citations

bulk RNA-seqstatistical model

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