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Ten Quick Tips for Deep Learning in Biology.

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An Analysis of New Expert Knowledge Scaling Methods for Biologically Inspired Computing., , , , и . ECAL (2), том 5778 из Lecture Notes in Computer Science, стр. 286-293. Springer, (2009)Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions., , , и . BioData Min., (2009)Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS., , , , , и . Bioinform., 26 (5): 694-695 (2010)Unsupervised Feature Construction and Knowledge Extraction from Genome-Wide Assays of Breast Cancer with Denoising Autoencoders., , , и . Pacific Symposium on Biocomputing, стр. 132-143. (2015)Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms., , , , , , , и . PLoS Comput. Biol., (2015)Enabling Personal Genomics with an Explicit Test of Epistasis., , , , , , , и . Pacific Symposium on Biocomputing, стр. 327-336. World Scientific Publishing, (2010)Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders., и . PSB, стр. 80-91. (2018)Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: a study of ADNI cohorts., , , , , , , и . BioData Min., (2016)Parameterized algorithms for identifying gene co-expression modules via weighted clique decomposition., , , , и . ACDA, стр. 111-122. SIAM, (2021)Development and evaluation of an open-ended computational evolution system for the creation of digital organisms with complex genetic architecture., , , , , и . IEEE Congress on Evolutionary Computation, стр. 2907-2912. IEEE, (2009)