Our research aims to address fundamental problems in both biomedical research and computer science by developing new tools tailored to rapidly emerging high-throughput sequencing technologies. Broadly, we seek to understand what genes define the complement of cell types and cell states within healthy tissue, how cells differentiate to their final fates, and how dysregulation of genes within specific cell types contributes to human disease. As computational method developers, we seek to both employ and advance the methods of machine learning, particularly for unsupervised analysis of high-dimensional data.
Most recently, I have focused on developing open-source software for the processing, analysis, and modeling of single-cell sequencing data. Key contributions in this area include LIGER, a general approach for integrating single-cell transcriptomic, epigenomic and spatial transcriptomic data; online iNMF, a scalable and iterative algorithm for single-cell data integration; and MultiVelo, a tool for modeling cell fate transitions from single-cell multi-omic data. I have applied these methods in collaboration with biological scientists to study stem cell differentiation, somatic cell reprogramming, and the mammalian brain.
The Welch Lab has openings for multiple positions, including Postdoctoral Fellow, PhD Student, Bioinformatician, and Software Engineer! (more info)
Neil and Mingjia pass their PhD qualifying exams and achieve candidacy
December 3, 2024Review paper about spatial transcriptomics in neuroscience published in Nature Neuroscience
November 23, 2024Collaborative paper with Baldwin lab published in JCI Insight
September 20, 2024Generative AI review paper published in JBMR
September 4, 2024IGVF consortium roadmap paper is published in Nature
August 15, 2024Hojae successfully defends her dissertation and earns her PhD in Electrical and Computer Engineering
July 23, 2024Chan-Zuckerberg Initiative awards a Data Insights grant to Joshua Welch
July 1, 2024Collaborative paper with Collins lab published in Nature Communications
June 19, 2024Perspective on AI for algorithmic biology is published in Cell Systems