Computational Genomics & Transcriptomics Laboratory

Research Interests

Radiogenomics

Radiogenomics is an emerging field that studies the relationship between imaging features and genomic data to improve the understanding, diagnosis, and treatment of diseases. Our lab focuses on identifying non-invasive biomarkers that can predict the molecular drivers of tumor progression. We employ radiomics to analyze glioblastoma through MRI scans and renal carcinoma via CT imaging. Additionally, we investigate regions of the brain exhibiting significant neurodegeneration in Alzheimer's disease, aiming to uncover the underlying mechanisms of this challenging condition.

Kavita Kundal

Phd-PMRF

Ishsirjan Kaur Chandok

MTECH

CRC Theranostics using AI/ML

Our lab is leveraging AI and ML to revolutionize Colorectal Cancer(CRC) treatment. We're exploring drug repurposing for both established and novel targets, identifying early diagnosis biomarkers, and analyzing genomic, transcriptomic, and multiomic data to understand disease variations. This research aims to develop highly personalized treatment strategies for CRC patients, improving healthcare outcomes and potentially transforming preventive interventions.

Avik Sengupta

PhD Scholar

Single-Cell Transcriptomics

Our current research focuses on using single-cell transcriptomics to study breast cancer at a molecular level. This approach allows us to analyze individual cancer cells' molecular profiles, revealing unique gene expression patterns and signaling pathways. By exploring cancer cell heterogeneity at a single-cell level, we aim to identify potential therapeutic targets within specific cell subpopulations, advancing our understanding of breast cancer biology and paving the way for personalized treatment strategies. Ultimately, our research aims to contribute to the development of targeted therapies and precision medicine for breast cancer patients.

Sushree Sangita Kar

PhD Scholar

Epigenomics

Epigenomics investigates the intricate interplay between epigenetic modifications and cancer development. It utilizes DNA methylation data, Chromatin Immunoprecipitation Sequencing (ChIP-seq), and Assay for Transposase-Accessible Chromatin Sequencing (ATAC-seq). We focus on high-throughput sequencing data, we aim to identify key epigenetic markers and pathways involved in cancer pathogenesis. Ultimately, this research aims to discover novel biomarkers for early cancer detection

Bhanu Teja Korra

PhD Scholar

Neuro-omics in ALS

Neuro-omics in Amyotrophic Lateral Sclerosis(ALS) holds a significant interest as it unveils the intricate molecular and cellular mechanisms underlying disease pathogenesis. By integrating genomics, transcriptomics, and proteomics, we seek to identify novel genetic mutations and genomic alterations that contribute to motor neuron degeneration. This approach facilitates the discovery of critical biomarkers for early diagnosis, potential therapeutic targets, and insights into disease progression.

Subashani

PhD Scholar

Mutation Signature Analysis in Cancer

We are leading a research project focused on identifying and analyzing mutation signatures associated with gene mutations across various cancer types and subtypes. Our current work focuses on identifying mutational signatures associated with ALKBH (AlkB homolog) and TLS (Translesion Synthesis) gene family. Leveraging extensive genomic datasets and advanced tools like Palimpsest, we are conducting comprehensive mutational signatures assessment. We are also developing a versatile pipeline adaptable to any cancer type or gene, integrating tools such as R, Python, Excel, and SQL for enhanced analysis.

Soumik Roy

MTECH