DeepKhib: A Deep-Learning Framework for Lysine 2-Hydroxyisobutyrylation Sites Prediction.

ABSTRACT: As a novel type of post-translational modification, lysine 2-Hydroxyisobutyrylation (K _hib ) plays an important role in gene transcription and signal transduction. In order to understand its regulatory mechanism, the essential step is the recognition of K _hib sites. Thousands of K _hib sites have been experimentally verified across five different species. However, there are only a couple traditional machine-learning algorithms developed to predict K _hib sites for limited species, lacking a general prediction algorithm. We constructed a deep-learning algorithm based on convolutional neural network with the one-hot encoding approach, dubbed CNN _OH . It performs favorably to the traditional machine-learni

SUBMITTER: Zhang L 

PROVIDER: S-EPMC7509169 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature