Article

A generalizable deep learning framework for inferring fine-scale germline mutation rate maps

2021-10-26

Abstract excerpt

Germline mutation rates are essential for genetic and evolutionary analyses. Yet, estimating accurate fine-scale mutation rates across the genome is a great challenge, due to relatively few observed mutations and intricate relationships between predictors and mutation rates. Here we present MuRaL ( Mu tation Ra te L earner), a deep learning framework to predict mutation rates at the nucleotide level using only...

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Literature Corpus work: 30d74bc8-0446-5043-bd89-d5b6e89a728c
DOI: 10.1101/2021.10.25.465689

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