Author

Surekha Bantumilli

University of North Carolina at Chapel HillORCID 0000-0002-3213-6688Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Organism:human· 2 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexandria J. ShumwayiD· 2 shared Caroline Beasley· 2 shared Grace LianiD· 2 shared Lee‐Ching ZhuiD· 2 shared Matthew R. SchaneriD· 2 shared Shehzad Z. SheikhiD· 2 shared Terrence S. FureyiD· 2 shared Chinmaya U. JoisaiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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2 shared papersGenomics

Alexandria J. ShumwayORCID

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2 papers

Recent·Most cited

GenomicsJCI InsightPeer-reviewedFeb 21, 2024

Aberrant miR-29 is a predictive feature of severe phenotypes in pediatric Crohn's disease

Alexandria J. Shumway, Michael T. Shanahan, Émilie Hollville…·Praveen Sethupathy

The paper identifies miR-29 as a predictive marker for severe phenotypes in pediatric Crohn's disease through miRNA analysis and validation in mice and human patients.

9 citations

humanbulk RNA-seq

𝕏 PostBluesky

BioinformaticsScientific ReportsPeer-reviewedFeb 1, 2024

Linking Gene Expression to Clinical Outcomes in Pediatric Crohn's Disease Using Machine Learning

Kevin A. Chen, Nina C. Nishiyama, Meaghan M. Kennedy Ng…·Shehzad Z. Sheikh

The paper uses machine learning to predict clinical outcomes in pediatric Crohn's disease by analyzing gene expression from ileal and colonic tissues.

10 citations

humanbulk RNA-seq

𝕏 PostBluesky