한국정보과학회:학술대회논문집 (Proceedings of the Korean Information Science Society Conference)
- 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (B)
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- Pages.17-21
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- 2007
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- 1598-5164(pISSN)
SVM을 사용한 약물 표적 단백질 예측
Drug Target Protein Prediction using SVM
- Jung, Hwie-Sung (Information and Communications University) ;
- Hyun, Bo-Ra (Information and Communications University) ;
- Jung, Suk-Hoon (Information and Communications University) ;
- Jang, Woo-Hyuk (Information and Communications University) ;
- Han, Dong-Soo (Information and Communications University)
- 발행 : 2007.10.26
초록
Drug discovery is a long process with a low rate of successful new therapeutic discovery regardless of the advances in information technologies. Identification of candidate proteins is an essential step for the drug discovery and it usually requires considerable time and efforts in the drug discovery. The drug discovery is not a logical, but a fortuitous process. Nevertheless, considerable amount of information on drugs are accumulated in UniProt, NCBI, or DrugBank. As a result, it has become possible to try to devise new computational methods classifying drug target candidates extracting the common features of known drug target proteins. In this paper, we devise a method for drug target protein classification by using weighted feature summation and Support Vector Machine. According to our evaluation, the method is revealed to show moderate accuracy
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