Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	Dr. Shuxiong Wang，Department of Mathematics, University of California, Irvine
Inviter:	刘亚锋副研究员
Title:	Optimization Methods for high-dimensional Transcriptomics Data Analysis
Time & Venue:	2020.01.08 16:00-17:00 Z311
Abstract:	The rapid development of single-cell RNA-seq sequencing technologies in recent years enables the studies of complex biological systems at an unprecedented resolution. As more datasets are generated, various computational methods have been proposed to reveal the heterogeneity of cells, infer gene-regulatory networks, and reconstruct the trajectories of cell lineages in development. In this talk, we intend to introduce the scRNA-seq approaches, review the typical scRNA-seq data analysis (including quality control, normalization, feature selection, dimensionality reduction, and clustering etc.), and illustrate the recent advances for multi-omics data analysis. In addition, we will present an optimization-based method for high-dimensional transcriptomics data analysis. Via benchmarking the proposed approach against the state-of-the-art methods on multiple datasets, we show the efficiency and scalability of optimization techniques for large-scale problems.