Efficient inference for sparse latent variable models of transcriptional regulation

@article{Dai2017EfficientIF,
  title={Efficient inference for sparse latent variable models of transcriptional regulation},
  author={Zhenwen Dai and Mudassar Iqbal and Neil D. Lawrence and Magnus Rattray},
  journal={Bioinformatics},
  year={2017},
  volume={33},
  pages={3776 - 3783}
}
Abstract Motivation Regulation of gene expression in prokaryotes involves complex co-regulatory mechanisms involving large numbers of transcriptional regulatory proteins and their target genes. Uncovering these genome-scale interactions constitutes a major bottleneck in systems biology. Sparse latent factor models, assuming activity of transcription factors (TFs) as unobserved, provide a biologically interpretable modelling framework, integrating gene expression and genome-wide binding data… 

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