Prediction of nitrated tyrosine residues in protein sequences by extreme learning machine and feature selection methods.

CONCLUSIONS: Comparing to other prediction models that used classic machine learning algorithms as prediction engines on the same datasets with their own optimal features, the optimal ELM-based prediction model produced much better results, indicating the superiority of the proposed model for the identification of nitrated tyrosine residues from protein sequences.
PMID: 29848272 [PubMed - as supplied by publisher]

Source: Combinatorial Chemistry and High Throughput Screening - May 30, 2018 Category: Chemistry Authors: Chen L, Wang S, Zhang YH, Wei L, Xu X, Huang T, Cai YD Tags: Comb Chem High Throughput Screen Source Type: research