Article

Integrating convolution and self-attention improves language model of human genome for interpreting non-coding regions at base-resolution

2021-09-06

Abstract excerpt

Interpretation of non-coding genome remains an unsolved challenge in human genetics due to impracticality of exhaustively annotate biochemically active elements in all conditions. Deep learning based computational approaches emerge recently to help interpretating non-coding regions. Here we present LOGO ( L anguage o f G en o me), a self-attention based contextualized pre-trained language model containing only...

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Literature Corpus work: a5fe6bbd-f178-59aa-9704-2dd0df64b41e
DOI: 10.1101/2021.09.06.459087

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