Doctoral Symposium Talk: Tulika Kakati

Abstract: Tulika Kakati's (Tezpur University, Expected 2020) research focuses on gene expression analysis using ML to identify biomarkers across disease state and the cell cycle. Tulika's work has used novel clustering methods and identification of border genes for co-expression analysis, as well as developing novel deep learning approaches to the identification of differentially expressed genes via DEGnet, validating all models across a number of gene expression datasets. Tulika has also investigated improving the computational efficiency of these methods via distributed computing, specifically with regards to the application of their clustering algorithms.

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