Advances in computer science and the explosion of large scale, quantitative experiments have created a data-driven revolution in immunology. I will present a few short vignettes on harnessing computation to decode the genetic and molecular mechanisms underlying immune function. First, I will introduce a new algorithm to assemble B-cell receptor (BCR) sequences from single cell RNA-seq data. Second, I will introduce a new method for inferring transcriptional states of immune cells during dynamic processes from single cell RNA-seq data. I will present the role of this algorithm in a recently published study to model B cells undergoing class switch recombination. The talk will include the necessary background needed for understanding the immunology topics presented. I will conclude my talk by introducing a few open problems in computational immunology and their implications towards improving human health.
Faculty Host: Hatice Osmanbeyoglu (Pitt)
Hosted by the Joint CMU-Pitt Ph.D. Program in Computational Biology and the Department of Computational and Systems Biology
Zoom Participation. See announcement.