DeepGRP: engineering a software tool for predicting genomic repetitive elements using Recurrent Neural Networks with attention

DeepGRP: engineering a software tool for predicting genomic repetitive elements using Recurrent Neural Networks with attention

Abstract Background Repetitive elements contribute a large part of eukaryotic genomes. For example, about 40 to 50% of human, mouse and rat genomes are repetitive. So identifying and classifying repeats is an important step in genome annotation. This annotation step is traditionally performed using...

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Bibliographic Details
Main Authors: Fabian Hausmann, Stefan Kurtz
Format: Article
Language:English
Published: BMC 2021-08-01
Series:Algorithms for Molecular Biology
Subjects:
Supervised Learning
Artificial Intelligence
Computational Predictions
Machine Learning Algorithms
Performance
Recurrent Neural Networks
Online Access:https://doi.org/10.1186/s13015-021-00199-0

Internet

https://doi.org/10.1186/s13015-021-00199-0

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