DeepCapTail: A Deep Learning Framework to Predict Capsid and Tail Proteins of Phage Genomes

Abid, D.; Zhang, L.

doi:10.1101/477885

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bioRxiv · 10.1101/477885

DeepCapTail: A Deep Learning Framework to Predict Capsid and Tail Proteins of Phage Genomes

Abid, D.·Zhang, L.

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Abstract

The capsid and tail proteins are considered the main structural proteins for phages and also their footprint since they exist only in phage genomes. These proteins are known to lack sequence conservation, making them extremely diverse and thus posing a major challenge to identify and annotate them in genomic sequences. In this study, we aim to overcome this challenge and predict these proteins by using deep neural networks with composition-based features. We develop two models trained with k-mer features to predict capsid and tail proteins respectively. Evaluating the models on two different testing sets shows that they outperform state-of-the-art methods with improved F-1 scores.

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Abid, D., Zhang, L.. 2018-11-23. DeepCapTail: A Deep Learning Framework to Predict Capsid and Tail Proteins of Phage Genomes. https://doi.org/10.1101/477885

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