In this talk, we will start with the introduction of a biological problem and show how we model it as a computational problem. Then, we will briefly describe the algorithm for solving the problem and present some evaluation results based on real biological data. All terms related to biology will be explained in the seminar, audience is not expected to have any biological knowledge. The biological problem we will discuss is related to something called "non-coding RNAs" (ncRNAs). Non-coding RNAs (ncRNAs) are RNA molecules that do not translate into proteins. They have been shown to be critical in many biological processes and related to some cancers and diseases. More and more ncRNAs were discovered and it is expected that ncRNAs may be as diverse as protein molecules. However, identifying ncRNAs in a laboratory is not easy. An alternative is to use computational approach to identify potential candidates from a genome (a long DNA sequence) for further verification. Most of these approaches are based on the observation that if two different ncRNAs are in the same family, they usually have similar "sequences" as well as "secondary structures". Based on this observation, we define the structural alignment problem to help solving the original biological problem. A special type of secondary structure called pseudoknots will also be introduced. The presence of pseudoknots in the structure makes the structural alignment problems computationally difficult to solve.
Dr. Yiu received a BSc in Computer Science from the Chinese University of Hong Kong, a MS in Computer and Information Science from Temple University, and a PhD in Computer Science from The University of Hong Kong. He was selected for the Teaching Excellence Award in the Department in 2001, 2003, 2004, 2005 and the Best Tutor Award in 1995 and 1996. He also received the Best Teacher Award of the Faculty of Engineering in 2005. Before he joined the Department as a faculty member, he has worked as an Analyst Programmer for a couple of years and has been involved in a number of projects (UFIA, FIT) led by Professor Chin. His current research interests include bioinformatics, computer security and cryptography.