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Dynamic modularity in protein interaction networks predicts breast cancer outcome

, , , , , , , , , and . Nature Biotechnology, 27 (2): 199--204 (Feb 1, 2009)
DOI: 10.1038/nbt.1522

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Mixture Model for Sub-Phenotyping in GWAS., , , and . Pacific Symposium on Biocomputing, page 363-374. World Scientific Publishing, (2012)Dynamic modularity in protein interaction networks predicts breast cancer outcome, , , , , , , , , and . Nature Biotechnology, 27 (2): 199--204 (Feb 1, 2009)Self-informed neural network structure learning., , and . ICLR (Workshop), (2015)Relative Variational Intrinsic Control., , , and . AAAI, page 6732-6740. AAAI Press, (2021)Learning more skills through optimistic exploration., , , , and . ICLR, OpenReview.net, (2022)Maxout Networks., , , , and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 1319-1327. JMLR.org, (2013)Theano: A Python framework for fast computation of mathematical expressions, , , , , , , , , and 103 other author(s). (2016)cite arxiv:1605.02688Comment: 19 pages, 5 figures.Improving Generative Adversarial Networks with Denoising Feature Matching., and . ICLR (Poster), OpenReview.net, (2017)Theano: new features and speed improvements, , , , , , , , and . (Nov 23, 2012)Fast Task Inference with Variational Intrinsic Successor Features., , , , , and . ICLR, OpenReview.net, (2020)