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Realistic in silico generation and augmentation of single cell RNA-seq data using Generative Adversarial Neural Networks

, , , , , , and . bioRxiv, (2018)Code is available: https://github.com/greenelab/deep-review/issues/906.

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Deep Learning and Random Forest-Based Augmentation of sRNA Expression Profiles., , and . ISBRA, volume 11490 of Lecture Notes in Computer Science, page 159-170. Springer, (2019)A systematic screen for protein-lipid interactions in Saccharomyces cerevisiae., , , , , , , , , and 8 other author(s). Molecular systems biology, (Nov 30, 2010)Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network., , , , , , , and . ML4H@NeurIPS, volume 158 of Proceedings of Machine Learning Research, page 38-53. PMLR, (2021)A semantic data integration methodology for translational neurodegenerative disease research., , , and . SWAT4LS, volume 2275 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)Deep Learning-Based Discrete Calibrated Survival Prediction., , , , , and . ICDH, page 169-174. IEEE, (2022)Uncertainty Estimation for Single-cell Label Transfer., and . COPA, volume 179 of Proceedings of Machine Learning Research, page 109-128. PMLR, (2022)Realistic in silico generation and augmentation of single cell RNA-seq data using Generative Adversarial Neural Networks, , , , , , and . bioRxiv, (2018)Code is available: https://github.com/greenelab/deep-review/issues/906.A systematic screen for protein--lipid interactions in Saccharomyces cerevisiae, , , , , , , , , and 8 other author(s). Mol. Syst. Biol., (2010)Oasis 2: improved online analysis of small RNA-seq data., , , , , , , , and . BMC Bioinform., 19 (1): 54:1-54:10 (2018)Deep Learning-Based Bias Transfer for Overcoming Laboratory Differences of Microscopic Images., , , , , , , , , and 2 other author(s). MIUA, volume 12722 of Lecture Notes in Computer Science, page 322-336. Springer, (2021)