Jagat S Chauhan

My interests lie in the field of genomics and integrating multi-omics approaches to understand cardiovascular disease biology and build prognostic models. I am working with Prof Charalambos Antoniades’s group on European Commission Horizon 2020 funded project named “Machine Learning and Artificial intelligence for Early detection of Stroke and Atrial Fibrillation (MAESTRIA)”.

I am involved in the analysis of RNA sequencing, genomic, radiomic (big data derived from the analysis of CT scans) , patient health outcomes data and integration of radiomics and transcriptomics data. The development and validation of novel tools for the assessment of cardiovascular disease risk and severity. Also involved in the data management and analysis strategy from a large programme (the Oxford Heart Vessels and Fat (ox-­HVF, www.oxhvf.com) that includes >100k patients with cardiac imaging and extensive tissue molecular phenotyping, linked with long-­‐term outcomes data through the UK national databases and international registries.

Background

I did my PhD in Computational Biology. During my PhD, I applied machine learning and Bioinformatics approaches to analyse and predict protein-small molecule interactions. I have developed a number of web servers and databases for the identification of ligand binding sites, predicting small molecule inhibitory activity, in silico screening and designing of drugs/analogues/chemicals using Bioinformatics and Chemoinformatics techniques. Then in 2014 I joined the Ludwig institute of cancer research, the Nuffield Department of Clinical Medicine (NDM) and the department of oncology, University of Oxford as a Postdoctoral research scientist and I have worked on understanding phenotypic heterogeneity and the molecular mechanisms that drive microenvironment-driven metastatic, and phenotypic drug-resistance in melanoma using Genomics, Bioinformatics and machine learning techniques.  I have been involved in processing, analyzing and integrating multi-omics/ sequencing data (Bulk & Single Cell RNA-Seq, ChIP-Seq, Proteomics, ATAC-Seq and Exome seq data) to understanding how tumor microenvironment factors like hypoxia, stress response and nutrient deprivation regulate phenotypic plasticity in melanoma, lung cancer and breast cancer. In addition to this I have also worked on pharmacogenomics project to in-silico screening most potential drug molecules using drug sensitivity data.