Keynote DTMBIOchange

Title: Gene regulatory network reconstruction using single cell transcriptomic data 

Short Bio

Dr. Kyoung-Jae Won received the B.S. and M.S. degrees in Electronics from Chung-Ang University, Korea in 1996, and 1998, respectively. He received his PhD in Electronics and Computer Science from the University of Southampton, UK in 2006. His main area was evolutionary computation. He worked at the University of Copenhagen in 2006 and the University of California San Diego (UCSD) from 2007 to 2010 as a postdoctoral researcher. During this time, he applied hidden Markov Models to various biological questions including epigenomics gene regulation. He worked at the School of Medicine, University of Pennsylvania as a Research Assistant Professor. Since 2018, he has worked at BRIC, University of Copenhagen as an Associate Professor. He has interest in developing computational algorithms for single cell genomic data.



Gene expression data has been widely used to infer gene regulatory networks (GRNs). Recent single-cell RNA sequencing (scRNAseq) data, containing the expression information of the individual cells (or status), are highly useful in blindly reconstructing regulatory mechanisms. However, it is still not easy to understand transcriptional cascade from large amount of expression data. Besides, the reconstructed networks may not capture the major regulatory rules.
Here, we propose a novel approach called TENET to reconstruct the GRNs from scRNAseq data by calculating causal relationships between genes using transfer entropy (TE). We show that known target genes have significantly higher TE values. Genes with higher TE values were more affected by various perturbations. Comprehensive benchmarking showed that TENET outperformed other GRN prediction algorithms. More importantly, TENET is uniquely capable of identifying key regulators. Applying TENET to scRNAseq during embryonic stem cell differentiation to neural cells, we show that Nme2 is a critical factor for 2i condition specific stem cell self-renewal. TENET identified new regulatory factors during autophagy and the progression of acute myeloid leukemia (AML).