I analyze orthogonal biomedical datasets and apply statistical and machine learning algorithms for biomarker and drug discovery in cancer, diabetes, obesity etc.
Find Out MoreMachine learning of genomics and clinical datasets (TCGA, RNA-seq, scRNA-seq, GWAS etc.) of millions of patients and customer datasets for biomarker and drug discovery in cancer, diabetes, obesity, Alzheimer’s etc.
On demand web app development with biomedical datasets for interactive visualization and statistical analysis on the fly. Apps are deployed in-house or Cloud (Amazon AWS, Microsoft Azure or Google Cloud)
Apply existing tools, integrate orthogonal high dimensional datasets or databases, mathematical models, AI and ML algorithms to solve complex data science problems and get actionable insights.
NGS Pipelines, GWAS, RNA-seq, Microarray, scRNA-seq, ChIP-seq, Variant Calling, Pathway Enrichment Analysis, Sequence Analysis, Phylogenetics, Computational Chemistry
Apply Python and R Programming to solve AI amd ML problems
Proficient in applying unsupervised and supervised machine learning tools to solve biomedical problems.
h-index: 22, i10-index: 27, #citations: 2100+, #papers: 40+