The long-term goal of our research is to elucidate
alternative isoform complexity in mammalian transcriptomes and proteomes
Our lab is broadly interested in computational biology and genomics of RNA processing and regulation, as well as their applications to human genetics, precision medicine, and cancer immunotherapy.
Mammalian cells generate astonishing regulatory diversity and complex phenotypes from a surprisingly small set of genes. We now know that considerable diversity is achieved by alternative processing and modifications of RNA. The long-term goal of our research is to elucidate alternative isoform complexity in mammalian transcriptomes and proteomes, and to understand how it is generated and its role in the regulation and function of complex genomes. We develop computational methods and genomic technologies for studying transcriptomic and proteomic complexity in bulk tissues and single cells (Nature Methods, 2019; American Journal of Human Genetics, 2019; Genome Biology, 2017; Nature Methods, 2016; PNAS, 2014; Genome Biology, 2013). We also integrate computational and genomic tools to elucidate RNA regulatory networks in health and disease (American Journal of Human Genetics, 2018; Genome Biology, 2016; Cell Reports, 2016; Elife, 2015; Cell Stem Cell, 2014; Molecular Cell, 2014; Neuron, 2014).
Active research topics include but are not limited to: computational methods for transcriptome analysis using second- and third-generation sequencing technologies; genomic technologies and computational methods for analyzing RNA processing and modifications using low-input or single-cell samples; studies of RNA regulatory networks in health and disease using large-scale RNA-seq data and protein-RNA interaction maps; genetic variation and evolution of transcriptome regulation and RNA processing; clinical RNA-seq technologies for disease diagnosis or early detection; multi-omic and clinical data integration for precision oncology and cancer immunotherapy.