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GNE: a deep learning framework for gene network inference by aggregating biological information
2019
BMC Systems Biology
The topological landscape of gene interaction networks provides a rich source of information for inferring functional patterns of genes or proteins. However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions. In particular, how to generate a unified vector representation to integrate diverse input data is a key challenge addressed here.
doi:10.1186/s12918-019-0694-y
pmid:30953525
pmcid:PMC6449883
fatcat:ivtugel7mnga3pzmsrvve653ii