An Information Entropy-Based Approach for Computationally Identifying Histone Lysine Butyrylation.

ABSTRACT: Butyrylation plays a crucial role in the cellular processes. Due to limit of techniques, it is a challenging task to identify histone butyrylation sites on a large scale. To fill the gap, we propose an approach based on information entropy and machine learning for computationally identifying histone butyrylation sites. The proposed method achieves 0.92 of area under the receiver operating characteristic (ROC) curve over the training set by 3-fold cross validation and 0.80 over the testing set by independent test. Feature analysis implies that amino acid residues in the down/upstream of butyrylation sites would exhibit specific sequence motif to a certain extent. Functional analysis suggests that histone butyrylation was most possibly associated with four pathways (systemic lupus erythemato

SUBMITTER: Huang G 

PROVIDER: S-EPMC7033570 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature