A novel gene selection method based on sparse representation and Max-Relevance and Min-Redundancy.

This article proposes a new method based on sparse representation and MRMR algorithm（SRCMRMR）, using the sparse representation coefficient to represent the relevance of genes and correlation between genes and categories. The SRCMRMR algorithm contains two steps. Firstly，the genes irrelevant to the classification target are removed by using sparse representation coefficient. Secondly, sparse representation coefficient is used to calculate the correlation between genes and the most representative gene with the highest evaluation. The former ones are under the influence of other genes, while the latter is selected through the improved MRMR algorithm. The effectiveness and stability of this method have been fully proved insome experiments.
PMID: 28128052 [PubMed - as supplied by publisher]

Source: Combinatorial Chemistry and High Throughput Screening - January 25, 2017 Category: Chemistry Authors: Chen M, He X, Duan SB, Deng YW Tags: Comb Chem High Throughput Screen Source Type: research