Author

Sharun Ramachandran

Indian Institute of Technology Bombay

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Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:ChIP-seq· 2 Organism:yeast· 2 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Nithya RamakrishnaniD· 2 shared Sibi Raj B. Pillai· 1 shared V. K. Dhanasekhar· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Nithya RamakrishnanORCID

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2 papers

Recent·Most cited

Multivariate Mutual Information based Feature Selection for Predicting Histone Post-Translational Modifications in Epigenetic Datasets

V. K. Dhanasekhar, Sharun Ramachandran, Sibi Raj B. Pillai, Nithya Ramakrishnan

This paper introduces multivariate mutual information (MMI) for selecting histone PTM features to predict epigenetic data, showing improved accuracy over traditional methods.

npj Systems Biology and Applications · Oct 30, 2026Peer-reviewedBioinformatics

An Explainable Machine Learning Approach to study the positional significance of histone post-translational modifications in gene regulation

Sharun Ramachandran, Nithya Ramakrishnan

This study uses explainable machine learning to identify critical histone PTMs and their positions in gene regulation using yeast ChIP-seq data.

bioRxiv · Feb 2, 2026 · PreprintBioinformatics