题目：An Interaction-Based Feature Selection and Classification Method for High-Dimensional Biological Data

报告人◼️：Professor Inchi HU(香港科技大学教授👋，商意昂4学术委员会主任)

Abstract Gene-gene interaction has gained increasing attention in studies of complex diseases. Its presence as an ubiquitous component of genetic architecture of common human diseases has been contemplated. However, the detection of gene-gene interaction is difficult due to combinatorial explosion. We present a novel feature selection method incorporating variable interaction. Several gene expression datasets are analyzed to illustrate our method, although it can also be applied to other types of high-dimensional data. The quality of variables selected is evaluated in two ways: first by classification error rates, then by functional relevance assessed using biological knowledge. We show that the classification error rates can be significantly reduced by considering interactions. Secondly, a sizable portion of genes identified by our classification rule for breast caner metastasis overlaps with those reported in the literature as disease associated and some of them have interesting biological implications. In summary, our interaction-based method can lead to substantial gain in biological insights as well as more accurate prediction.

时间🕵🏿‍♂️🏌🏼‍♀️：2012年11月28日（周三）下午15:30开始

地点：数学系致远楼102室