Author

Shayantan Banerjee

Indian Institute of Technology MadrasORCID 0000-0003-4698-9435Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Shayantan Banerjee2 papers · Indian Institute of Technology Bombay

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Assay:whole-exome sequencing· 2 Research Focus:differential expression· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Karthik RamaniD· 3 shared Anjana Anilkumar SitharaiD· 1 shared Balaraman RavindraniD· 1 shared Devi Priyanka MaripuriiD· 1 shared Keerthika MoorthyiD· 1 shared Malvika SudhakariD· 1 shared Mohammed InayatullahiD· 1 shared Philge PhilipiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersBioinformatics

Karthik RamanORCID

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3 papers

Recent·Most cited

Tumor-Infiltrating Lymphocytes Display Prognostic Signatures Associated with Chemotherapy Response in TNBC Patients

Shayantan Banerjee, Vijay Kumar Tiwari, Karthik Raman, Mohammed Inayatullah

This study identifies 30 TIL-derived gene markers with prognostic value for chemotherapy response in TNBC, validated across multiple datasets with AUROC scores above 0.65.

iScience · Jun 1, 2026Peer-reviewedCancer Biology

iCOMIC: a graphical interface-driven bioinformatics pipeline for analyzing cancer omics data

Anjana Anilkumar Sithara, Devi Priyanka Maripuri, Keerthika Moorthy, Sai Sruthi Amirtha Ganesh, Philge Philip, Shayantan Banerjee, Malvika Sudhakar, Karthik Raman

iCOMIC is a user-friendly bioinformatics pipeline for analyzing cancer omics data, providing insightful statistics and high accuracy in variant calling.

NAR Genomics and Bioinformatics · Jul 9, 2022Peer-reviewedBioinformatics

Sequence neighborhoods enable reliable prediction of pathogenic mutations in cancer genomes

Shayantan Banerjee, Karthik Raman, Balaraman Ravindran

This study develops NBDriver, a tool that uses sequence neighborhoods to predict pathogenic mutations in cancer genomes, outperforming existing methods in identifying driver mutations.

Cancers · May 14, 2021Peer-reviewedBioinformatics