Nita Parekh

Research Interest

  • COVID-19

    • Demographic analysis of SARS-COV-2 mutations
    • Analysis of chest X-rays and CT-scan images using machine learning approaches for diagnosis of COVID-19

  • Cancer Genomics

    • Genetic variation analysis (CNVs and SSVs) in DLBCL using next generation sequence (NGS) data
    • Integration of DNA methylation, differential gene expression and variation data for identifying diagnostic and prognostic markers in breast cancer
    • Machine learning (ML) approaches for cancer subtype classification using transcriptomics and methylation data

  • Biological Network Analysis

    • Protein Contact Networks (residue-residue interaction networks) for detection of structural repeats, residues involved in protein-protein/DNA/RNA interactions, domain identification, etc.
    • Gene co-expression network analysis of abiotic and biotic stress conditions in rice (microarray and RNASeq data) for identifying stress-specific biomarkers.

Recent Updates

PhD position: Please email your CV to apply for the position

Contact: Nita Parekh, Associate Professor
Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology-Hyderabad