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변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
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RISS 인기검색어
- 검색키워드
- 저자 : Mina Gachloo (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition
Mina Gachloo,Yuxing Wang,Jingbo Xia 한국유전체학회 2019 Genomics & informatics Vol.17 No.2
Prediction of the relations among drug and other molecular or social entities is the main knowledge discovery pattern for the purpose of drug-related knowledge discovery. Computational approaches have combined the information from different sources and levels for drug-related knowledge discovery, which provides a sophisticated comprehension of the relationship among drugs, targets, diseases, and targeted genes, at the molecular level, or relationships among drugs, usage, side effect, safety, and user preference, at a social level. In this research, previous work from the BioNLP community and matrix or matrix decomposition was reviewed, compared, and concluded, and eventually, the BioNLP open-shared task was introduced as a promising case study representing this area.
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A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition
Gachloo, Mina,Wang, Yuxing,Xia, Jingbo Korea Genome Organization 2019 Genomics & informatics Vol.17 No.2
Prediction of the relations among drug and other molecular or social entities is the main knowledge discovery pattern for the purpose of drug-related knowledge discovery. Computational approaches have combined the information from different sources and levels for drug-related knowledge discovery, which provides a sophisticated comprehension of the relationship among drugs, targets, diseases, and targeted genes, at the molecular level, or relationships among drugs, usage, side effect, safety, and user preference, at a social level. In this research, previous work from the BioNLP community and matrix or matrix decomposition was reviewed, compared, and concluded, and eventually, the BioNLP open-shared task was introduced as a promising case study representing this area.
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