下記要領で、第11回JSBiバイオインフォマティクス学会北海道支部会セミナーを開催します。登録不要・参加無料です。多数のご参加をお待ちしております。関心ありそうな方へも転送していただけると幸いです。
日時：平成23年2月9日(水) 14:30-17:00
場所：北海道大学 情報科学研究科棟A12
http://www.ist.hokudai.ac.jp/facilities/index.php?floor_key=1
講師：Meena K. Sakharkar教授 (筑波大学生命環境科学研究科)
Kishore R. Sakharkar教授 (マレーシア理科大学)
プログラム：
14:30-15:30
Drug discovery - piecing together the information puzzle
Professor Meena K. Sakharkar,
School of Life and Environmental Sciences University of Tsukuba
Abstract:
Accumulated knowledge on genomic information, systems biology, and disease mechanisms provide an unprecedented opportunity to elucidate the genetic basis of diseases, and to discover novel therapeutic targets from genomic data. With hundreds to a few thousand potential targets available in the human genome alone, and the rise in the role of
multi-drug therapies for complex diseases, there is an urgent need to understand the relationships between diseases and genes, and drugs and targets. These data will help inform and guide future drug discovery processes. In this talk, I will present some data-mining approaches used in our lab in this direction.
15:45～16:45
Novel therapeutic strategies against drug resistant pathogens
Professor Kishore R. Sakharkarm, University Sains Malaysia
Abstract:
Antibiotic resistance poses a serious threat to the treatment of certain bacterial infections, and novel approaches are needed for the development of the next generation of antibiotics. Alongside, the extensive use of antimicrobial agents has resulted in emergence of pan-drug resistant bacteria. With different kinds of 'omics' data that are now available, complementary computational approaches can be powerful means of obtaining short-lists of putative targets for further experimental validation and drug discovery. Concurrently, the strategy of combining antibiotics with phytochemicals may have ramifications for the treatment of multi-drug-resistant organisms. This talk presents a two-way integrative computational-experimental approach that provides a rational schema for drug discovery, specifically, towards target prioritization and combination therapy. These integrative approaches may provide novel therapeutic options for treatment of bacterial infections.
