5th Canadian Student Conference 
on Biomedical Computing and Engineering

Information Distance From a Question to an Answer

Ming Li, Canada Research Chair in Bioinformatics, University of Waterloo

We know how to measure the distance from Toronto to Amsterdam. However, do you know how to measure the distance between two information carrying entities? For example: two genomes, two music scores, two programs, two articles, two emails, or from a question to an answer? Furthermore, such a distance measure must be application-independent, must be universal in the sense it is provably better than all other distances, and must be applicable.

From a simple and accepted assumption in thermodynamics, we have developed such a theory. I will present this theory and its applications. In particular, we will a new application of the theory: a question answering system.

Short Bio:

Ming Li is a Canada Research Chair in Bioinformatics and a University Professor at the University of Waterloo. He is a fellow of the Royal Society of Canada, ACM, and IEEE. He is a recipient of Canada's E.W.R. Steacie Fellowship Award in 1996, and the 2001 Killam Fellowship. Together with Paul Vitanyi they have pioneered the applications of Kolmogorov complexity and co-authored the book "An Introduction to Kolmogorov Complexity and Its Applications". In particular, his work on information distance and normalized information distance has found many applications in document comparison, genome evolution, time series analysis, as well as Question and Answer search engine on the internet. He is a co-managing editor of Journal of Bioinformatics and Computational Biology.

Structural Variation Discovery in High Throughput Sequenced Genomes and Transcriptomes

S. Cenk Sahinalp, Canada Research Chair in Computational Genomics, Simon Fraser University

Recent studies show that along with single nucleotide polymorphisms and small indels, larger structural variants contribute significantly to human genetic diversity. The realization of new ultra-high-throughput sequencing platforms now makes it feasible to detect the full spectrum of genomic variation among many individual genomes, including cancer patients and others suffering from diseases of genomic origin. Conventional algorithms for identifying structural variation (SV) have not been designed to handle the short read lengths and the errors implied by the "next-gen" sequencing (NGS) technologies. In this talk we will describe combinatorial formulations for the SV detection between a reference genome and a high throughput paired-end sequenced individual genome. We will provide efficient algorithms for each of the formulations we give, which all turn out to be fast and quite reliable; they are also applicable to all next-gen sequencing methods and traditional capillary sequencing technology.

Short Bio:

Cenk Sahinalp is a Professor of Computing Science at Simon Fraser University, Burnaby BC, an associate faculty at the Department of Molecular Biology and Biochemistry and a visiting scientist at the Department of Genome Sciences, University of Washington. His research focuses on problems in sequence alignment, search and comparison, biomolecular sequence analysis with emphasis on structural variation detection through the use of high throughput sequencing, RNA structure and interaction prediction, biomolecular network analysis and small molecule bioinformatics. He is a Canada Research Chair, a Michael Smith Foundation Scholar and has been a recipient of an NSF Career Award in theoretical computer science. He has served /will serve as the PC chair of the Combinatorial Pattern Matching (CPM) Conference in 2004, the general chair of the RECOMB Conference in 2011, the area chair on sequence analysis, next-gen sequencing, RNA structure prediction, etc. for a number of conferences including ISMB and PSB.

Title TBA

Nobuhiko Hata, Associate Professor of Radiology, Harvard Medical School

TBA

Short Bio:

Nobuhiko Hata is currently an Associate Professor of Radiology at Harvard Medical School, Technical Director of the Image Guided Therapy Program at Brigham and Women’s Hospital, and Director of the Surgical Navigation and Robotics Laboratory. His research focus has been on medical image processing and robotics in image-guided surgery. His major achievements include neurosurgical navigation combined with ultrasound imaging, surgical robot for magnetic resonance imager, and motion-adaptable surgical robot for image-guided therapy. More importantly, he developed key technology in many “the first” therapy in MRI-guided therapy; MR-guided prostate biopsy, MR-guided laser ablation therapy of brain tumor, and MR-guided microwave ablation therapy of liver tumor. In recognition of his achievements in image guided therapy, he received Minister’s Award from the Japanese minister of Education, Culture, Sports, Science and Technology in 2005.