报告题目：Application of metamorphic testing to bioinformatics software
报告人：Joshua W. K. Ho (何永基)
Dr Joshua W. K. Ho (何永基) is an Associate Professor in the School of Biomedical Sciences at the University of Hong Kong (HKU). Dr Ho completed his BSc (Hon 1, Medal) and PhD in Bioinformatics from the University of Sydney, and undertook postdoctoral research at the Harvard Medical School.
His research focuses on developing fast and reliable bioinformatics methods to identify the genetic cause and mechanism of various human diseases using a range of approaches such as whole genome sequencing, single-cell RNA-seq, ChIP-seq, machine learning, systems biology, cloud computing, and software testing and quality assurance. Dr Ho has over 70 publications, including first or senior-author papers in leading journals such as Nature, Genome Biology, Nucleic Acids Research and Science Signaling. His research excellence has been recognized by the 2015 NSW Ministerial Award for Rising Star in Cardiovascular Research, the 2015 Australian Epigenetics Alliance’s Illumina Early Career Research Award, and the 2016 Young Tall Poppy Science Award.
In this talk, we will discuss a largely ignored, yet highly important problem in biomedical research and clinical translation, verification and validation of bioinformatics software. Next generation sequencing (NGS)-based genomics, and other image- or senor-based big data are now ubiquitous in almost all areas of biomedical research, and is beginning to be used in translational applications to support clinical decision making.
It is important that these biomedical big data are being analysed by reliable bioinformatics algorithms and software, as incorrectly computed results may lead to wrong biological conclusions, and subsequently misguide downstream experiments or clinical decisions. Over the last decade, I have been involved in using a state-of-the-art software testing method, Metamorphic Testing (MT), to test various bioinformatics programs involved in genome medicine applications. I will summarise our experience in applying MT in bioinformatics applications, and discuss some open challenges in this area.