论文信息 - Bayesian deep learning for single-cell analysis - 字舞流文

Bayesian deep learning for single-cell analysis

A recent approach for single-cell RNA-sequencing data uses Bayesian deep learning to correct technical artifacts and enable accurate and multifaceted downstream analyses.

Casey S Greene | Gregory P Way

[1] Anne E Carpenter,et al. Opportunities and obstacles for deep learning in biology and medicine , 2017, bioRxiv.

[2] Kevin R. Moon,et al. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion , 2018, Cell.

[3] Michael I. Jordan,et al. Deep Generative Modeling for Single-cell Transcriptomics , 2018, Nature Methods.

[4] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .

[5] Fabian J Theis,et al. The Human Cell Atlas , 2017, bioRxiv.

[6] R. Irizarry,et al. Missing data and technical variability in single‐cell RNA‐sequencing experiments , 2018, Biostatistics.