Ensemble deep learning in bioinformatics-Reference-Cited by-同舟云学术

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Ensemble deep learning in bioinformatics

Published:2020-08-17 Issue:9 Volume:2 Page:500-508
ISSN:2522-5839
Container-title:Nature Machine Intelligence
language:en
Short-container-title:Nat Mach Intell

Author:

Cao Yue,Geddes Thomas Andrew,Yang Jean Yee Hwa,Yang Pengyi^ORCID

Funder

Department of Education and Training | Australian Research Council

Department of Health | National Health and Medical Research Council

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Software

Link

https://www.nature.com/articles/s42256-020-0217-y.pdf

Reference107 articles.

1. Larranaga, P. et al. Machine learning in bioinformatics. Briefings Bioinform. 7, 86–112 (2006).

2. Eraslan, G., Avsec, Ž., Gagneur, J. & Theis, F. J. Deep learning: new computational modelling techniques for genomics. Nat. Rev. Genet. 20, 389–403 (2019).

3. Camacho, D. M., Collins, K. M., Powers, R. K., Costello, J. C. & Collins, J. J. Next-generation machine learning for biological networks. Cell 173, 1581–1592 (2018).

4. Hansen, L. K. & Salamon, P. Neural network ensembles. IEEE Trans. Pattern Anal. Mach. 12, 993–1001 (1990).

5. Yang, P., Hwa Yang, Y., Zhou, B. B. & Zomaya, A. Y. A review of ensemble methods in bioinformatics. Curr. Bioinform. 5, 296–308 (2010).

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