藉由生物晶片與網路流量方法來預測藥物標的
碩士 === 國立清華大學 === 資訊系統與應用研究所 === 98 === System approach for medicine discovery is an emerging discipline in systems biology that aims at integrating large scale of the interaction data and experimental data to elucidate diseases. It also raises new issues in the drug discovery and design in developm...
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| Format: | Others |
| Language: | en_US |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/85957276845823735668 |
| Summary: | 碩士 === 國立清華大學 === 資訊系統與應用研究所 === 98 === System approach for medicine discovery is an emerging discipline in systems biology that aims at integrating large scale of the interaction data and experimental data to elucidate diseases. It also raises new issues in the drug discovery and design in development process for cancer treatment. However, drug target are still a trial-and-error experimental stage in clinical testing and it is a challenging task to develop a prediction model that can systematically detect the possible drug targets and their combinations to deal with a complex disease. We present a network flow-based approach to identify the effective drug targets and reduce the search space for drug target combination comparing with exhaustive search. We use the prostate cancer microarray data and DrugBank database as our test domain. We successfully identify potential drug targets which are strongly related to the well known drugs for prostate cancer treatment and also discover more potential drug targets and their combinations which attract the attention to biologists at present.
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