CAREER: Information-Theoretic Methods for RNA Analytics

University Of Washington, Seattle WA

Investigators

Abstract

The development of high-throughput sequencing has ushered in a new era in molecular biology, enabling inexpensive study of the genome. Furthermore, in recent years, RNA sequencing has enhanced our ability to quantify the dynamics of gene expression with transcript-level precision and single-cell resolution. This has applications in diverse areas like evolutionary biology, developmental biology, medical transcriptomics as well as synthetic biology. These advances in biotechnology necessitate corresponding advances in the development of computational algorithms that perform inference on these new datasets. Information theory offers a natural lens to study such problems as it can quantify the amount of data required to make accurate inferences, as well as leading to optimality. The main research objective of this project is to adapt, apply and create new information-theoretic and algorithmic methods to solve inference problems arising in RNA sequence analytics. The project will also have a significant educational component to integrate these new discoveries into graduate and undergraduate courses that can expose electrical engineering and computer science students to sequencing problems, in addition to exposing high-school and undergraduate students to this research area by outreach and mentoring. The project will study inference problems at two different levels of RNA-sequencing: assembly and downstream analytics. The typical method for RNA-sequencing involves fragmentation of RNA into short fragments that are then sequenced. The first thrust of this project will be in studying the informational limits and algorithms for this ?assembly? problem, particularly in studying the role of errors and repeated regions in the genome. The second thrust will be to study informational limits and algorithms for the downstream task of utilizing single-cell RNA-sequence data to understand gene-regulation and cell-differentiation.