At Sengupta Lab, we make use of state of the art Big Data mining and Machine Learning techniques to address computational challenges arising from the field of Genomics.

We closely collaborate with clinicians at leading hospitals to build better predictive models for cancer survival, drug resistance in infection and label-free identification of circulating tumor cells.

FiRE, assigns a rareness score to every individual expression profile under study in a matter of seconds.

Posted 14 Nov 2018

AutoImpute, learns inherent distribution of input scRNA-seq data and imputes missing values accordingly with minimal modification to the biologically silent genes.

Posted 13 Nov 2018

Shreya Mishra joins the group for Ph.D.

Posted 21 Jun 2018

Our dream project, CellAtlasSearch, the first single cell search engine is now published by Nucleic Acids Research

Posted 21 May 2018
Published 09 Nov 2018
Published 05 Nov 2018
In Press
Structure aware Principal Component Analysis for single cell RNA-seq data
Lall et al. Journal of Computational Biology 2018
Published 22 May 2018
CellAtlasSearch: a scalable search engine for single cells
Srivastava et al. Nucleic Acids Research 2018
Published 21 May 2018
Published 18 Jan 2018
Published 20 Mar 2017
Published 29 Jun 2016