ISCB-Asia/SCCG 2012, session on Workflows and the Cloud for Reproducible Computing


Tin-Lap Lee
Chinese University of Hong Kong

GDSAP – A Galaxy-based platform for large-scale genomics analysis

Abstract

The big data derived from next generation sequencing experiments makes efficient data mining strategies indispensible. Despite the plummeting costs of sequencing, the downstream processes create financial and bioinformatics challenges for many biomedical scientists. To alleviate this major stumbling block, we have established a Galaxy-based platform known as Genomic Data Submission and Analytical Platform (GDSAP) for fast and efficient genomic data analysis. The main objectives are to provide enhanced functionality in additional to the original Galaxy functions, including enhanced NGS tools such as the SOAP suite of assembly tools, Taverna workflows and customized public instances through seamless integration with SBS-UCSC genome database mirror and BGI’s GigaDB genomic database through the GigaScience journal portal. We plan to link global data networks such as GLORIAD (Global Ring Network for Advanced Application Development) and link Aspera to our platform to further improve the network traffic capacity. Taken together, the CBIIT Galaxy platform will serve as an important Galaxy portal for biomedical scientist in Asia and around the globe.

Biography

Dr. Tin L Lee is an Associate Professor in the School of Biomedical Sciences, Faculty of Medicine at the Chinese University of Hong Kong. He has previously conducted research at National Institutes of Health (NIH) in the United States for 10 years and was a Staff Scientist at the Laboratory of Clinical Genomics, National Institutes of Child Health and Human Development (NICHD) and Project Coordinator at National Center for Biotechnology Information (NCBI).

His research interests include developmental biology and biomedical informatics. Using male germ cells as model system, he identified genes and molecular networks that govern cellular differentiation and proliferation, which are fundamental process leading to normal or disease states. He also developed algorithms and databases to facilitate genomic data mining, including SAGEcluster, GermSAGE, GonadSAGE and TileMapper. Recently his group has identified a long non-coding RNA candidate known as Spga-lncRNA1/2 that controls Spermatogonial Stem Sell (SSC) differentiation. His works have been recognized NIH Merit Award, The NIH Fellows Award for Research Excellence and young scholar awards from American Association for Cancer Research and American Nanomedicine Society.