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Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks

Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability method...

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發表在:PLoS Comput Biol
Main Authors: Koo, Peter K., Majdandzic, Antonio, Ploenzke, Matthew, Anand, Praveen, Paul, Steffan B.
格式: Artigo
語言:Inglês
出版: Public Library of Science 2021
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在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC8118286/
https://ncbi.nlm.nih.gov/pubmed/33983921
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1008925
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