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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.5 No.3
- 발행연도
- 2011.9
- 수록면
- 257 - 268 (12page)
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초록· 키워드
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Machine learning and data mining have found many applications in biological domains, where we look to build predictive models based on labeled training data. However, in practice, high quality labeled data is scarce, and to label new data incurs high costs. Transfer and multitask learning offer an attractive alternative, by allowing useful knowledge to be extracted and transferred from data in auxiliary domains helps counter the lack of data problem in the target domain. In this article, we survey recent advances in transfer and multitask learning for bioinformatics applications. In particular, we survey several key bioinformatics application areas, including sequence classification, gene expression data analysis, biological network reconstruction and biomedical applications.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. DATA MINING IN BIOINFORMATICS: A SURVEY OF PROBLEMS
Ⅲ. BIOLOGICAL SEQUENCE ANALYSIS
Ⅳ. SYSTEMS BIOLOGY
Ⅴ. BIOMEDICAL APPLICATIONS
Ⅵ. DATA SETS FOR TRANSFER LEARNING
Ⅶ. SUMMARY
Ⅷ. CONCLUSION AND FUTURE WORK
ACKNOWLEDGMENT
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2013-569-000763963