November 17, 2017 conference-paper Open access Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders Pacific Symposium on Biocomputing (PSB) DOI: 10.1142/9789813235533_0008 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 4 stored of 224 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Benchmarking variational AutoEncoders on cancer transcriptomics data 2023 PLoS ONE article Biochemistry, Genetics and Molecular Biology Gene expression and cancer classification Open access 18 citations Benchmarking Variational AutoEncoders on cancer transcriptomics data 2023 bioRxiv (Cold Spring Harbor Laboratory) preprint Biochemistry, Genetics and Molecular Biology Gene expression and cancer classification Open access 4 citations Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models 2023 Nature Biotechnology article Biochemistry, Genetics and Molecular Biology Bioinformatics and Genomic Networks Open access 109 citations Automatic Gene Function Prediction in the 2020’s 2020 Genes article Biochemistry, Genetics and Molecular Biology Bioinformatics and Genomic Networks Open access 38 citations 4 results References 0