Improved analysis methods for RNA-seq

Methods to handle large genomic data sets

Methods to probe cancer genomes

Understanding the 3D structure of the human genome

Toward an Automated RNA-seq Bioinformatician

Measurement of gene expression is an indispensable tool for understanding biological systems. Analysis of gene expression from modern genomic sequencing technologies, such as RNA-seq, requires the use of sophisticated software which typically have a large number of user-settable parameters that influence how the analysis algorithm performs. Scientists, biologists, and clinical researchers must often tune these parameters by hand or through other ad hoc means. The goal of this project is to automate this process by designing and implementing a framework for automatically learning high-performing parameters for gene expression analysis software.