DocumentCode :
3458025
Title :
Improving prediction of drug therapy outcome via integration of time series gene expression and Protein Protein Interaction network
Author :
Qian, Liwei ; Zheng, Haoran
Author_Institution :
Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2012
fDate :
18-20 Aug. 2012
Firstpage :
12
Lastpage :
16
Abstract :
Drug therapy to patients is often with partial success, and has been associated with a number of adverse reactions. Prediction of patients´ response to therapy at the early stage of the treatment is crucial to avoiding those unnecessary adverse reactions. In this paper, a new approach that integrates time series gene expression and Protein Protein Interaction (PPI) network is presented to improve the prediction of patients´ response to drug therapy. Experimental results showed that our method outperformed previous approaches. The method proposed here offers a huge potential for applications in pharmacogenomics and medicine.
Keywords :
complex networks; drugs; genetics; hidden Markov models; medical computing; patient treatment; support vector machines; time series; PPI network; drug therapy outcome prediction; medicine; patient treatment response; pharmacogenomics; protein-protein interaction network; time series gene expression; Drugs; Gene expression; Hidden Markov models; Proteins; Time series analysis; PPI network; clinical studies; gene expression; time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems Biology (ISB), 2012 IEEE 6th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-4396-1
Electronic_ISBN :
978-1-4673-4397-8
Type :
conf
DOI :
10.1109/ISB.2012.6314105
Filename :
6314105
Link To Document :
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