Malvika Sudhakar

iCOMIC a graphical interface driven bioinformatics pipeline for analyzing cancer omics data
Towards Personalized Cancer treatment
Multi-omic data helps improve prediction of personalised tumor suppressors and oncogenes
Novel ratio-metric features enable the identification of new driver genes across cancer types
Machine Learning Applications for Mass Spectrometry-Based Metabolomics
Mycobacterium tuberculosis (Mtb) lipid–mediated lysosomal rewiring in infected macrophages modulates intracellular Mtb trafficking and survival.
Novel ratio-metric features enable the identification of new driver genes across cancer types