Speaker: Zhili Qiao, PhD Candidate, Department of Statistics, Iowa State University
Title: Some Clustering Methods for Omics Data
Abstract: The advent of high-throughput sequencing technologies has significantly facilitated omics research over the past two decades, generating a vast volume of data. Unsupervised learning technologies such as cluster analysis serve as powerful tools to uncover hidden patterns and associations in omics data. However, the intricate natural structure and unique characteristics of omics data often make generic clustering methods inefficient or unsuitable.
