Multi-task learning for the simultaneous reconstruction of the human and mouse gene regulatory networks
Published 2020 View Full Article
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Title
Multi-task learning for the simultaneous reconstruction of the human and mouse gene regulatory networks
Authors
Keywords
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Journal
Scientific Reports
Volume 10, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-12-18
DOI
10.1038/s41598-020-78033-7
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- (2019) Dayanne M. Castro et al. PLoS Computational Biology
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- (2017) Adrian M Altenhoff et al. NUCLEIC ACIDS RESEARCH
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- (2016) Lisa M. Breckels et al. PLoS Computational Biology
- ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks
- (2015) Gianvito Pio et al. BMC BIOINFORMATICS
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- (2015) Michelangelo Ceci et al. PLoS One
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- (2014) Liang Ge et al. Statistical Analysis and Data Mining
- Dealing with spatial autocorrelation when learning predictive clustering trees
- (2012) Daniela Stojanova et al. Ecological Informatics
- Wisdom of crowds for robust gene network inference
- (2012) Daniel Marbach et al. NATURE METHODS
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- (2012) Chun-Wei Seah et al. IEEE Transactions on Cybernetics
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- (2011) C. A. Penfold et al. Interface Focus
- A Survey on Transfer Learning
- (2009) Sinno Jialin Pan et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- Universal protein-binding microarrays for the comprehensive characterization of the DNA-binding specificities of transcription factors
- (2009) Michael F Berger et al. Nature Protocols
- ChIP–seq: advantages and challenges of a maturing technology
- (2009) Peter J. Park NATURE REVIEWS GENETICS
- Gene regulatory network inference: Data integration in dynamic models—A review
- (2008) Michael Hecker et al. BIOSYSTEMS
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