JCSE, vol. 5, no. 3, pp.257-268, 2011

DOI: 10.5626/JCSE.2011.5.3.257/

A Survey of Transfer and Multitask Learning in Bioinformatics

Qian Xu, Qiang Yang
Hong Kong University of Science and Technology, Kowloon, Hong Kong, China

Abstract: 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.

Keyword: Transfer learning; Bioinformatics, Data mining

Full Paper:   287 Downloads, 2445 View