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DeepGRP: engineering a software tool for predicting genomic repetitive elements using Recurrent Neural Networks with attention
2021
Algorithms for Molecular Biology
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 alignment based methods, either in a de novo approach or by aligning the genome sequence to a species specific set of repetitive sequences. Recently, Li (Bioinformatics 35:4408–4410, 2019) developed a novel
doi:10.1186/s13015-021-00199-0
fatcat:i4c5y6cm4zahzoogftd2djl4re