My main interest is in computational biology, especially the applications of machine learning to biological problems.
My current work involves developing methods for analyzing single cell RNA sequencing data.
I have previously worked on using convolutional neural networks to identify sequence motifs that affect alternative splicing.
I am advised by Prof. Georg Seelig.
UNCURL-App, a web-based platform for analyzing single cell RNA-seq data
CellMeSH, a literature-based database for cell type identification
UNCURL, a pre-processing method for single cell RNA-seq data
Zhang, Yue*, Shunfu Mao*, Sumit Mukherjee, Sreeram Kannan, and Georg Seelig. “UNCURL-App: Interactive Database-Driven Analysis of Single Cell RNA Sequencing Data.” BioRxiv, April 16, 2020, 2020.04.15.043737. https://doi.org/10.1101/2020.04.15.043737.
Mukherjee, Sumit*, Yue Zhang*, Joshua Fan, Georg Seelig, and Sreeram Kannan. “Scalable Preprocessing for Sparse ScRNA-Seq Data Exploiting Prior Knowledge.” Bioinformatics 34, no. 13 (July 1, 2018): i124–32. https://doi.org/10.1093/bioinformatics/bty293.
Criscione, Steven W., Marco De Cecco, Benjamin Siranosian, Yue Zhang, Jill A. Kreiling, John M. Sedivy, and Nicola Neretti. “Reorganization of Chromosome Architecture in Replicative Cellular Senescence.” Science Advances 2, no. 2 (February 1, 2016): e1500882. doi:10.1126/sciadv.1500882.
Criscione, Steven W., Yue Zhang, William Thompson, John M. Sedivy, and Nicola Neretti. “Transcriptional Landscape of Repetitive Elements in Normal and Cancer Human Cells.” BMC Genomics 15, no. 1 (July 11, 2014): 583. doi:10.1186/1471-2164-15-583.
I attended Brown University from 2011-2015, graduating with an Sc.B in Math and Computer Science. There, I worked with Prof. Nicola Neretti on quantifying repetitive elements in cells and tools for reconstructing 3D chromosome structure.