Identification of cell cycle-regulated genes by convolutional neural network.

Identification of cell cycle-regulated genes by convolutional neural network.
Comb Chem High Throughput Screen. 2017 Apr 17;:
Authors: Liu C, Cui P, Huang T
Abstract
BACKGROUND: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big problems in cell cycle-regulated gene detection.
METHODS: Here, a computational framework called DLGene was proposed for cell cycle-regulated gene detection. It is based on the convolutional neural network, a deep learning algorithm representing raw form of data pattern without assumption of their distribution. First, the expression data was transformed to categorical state data to denote the changing state of gene expression, and four different expression patterns were revealed for the reported cell cycle-regulated genes. Then, DLGene was applied to discriminate the non-cell cycle gene and the four subtypes of cell cycle genes. Its performances were compared with six traditional machine learning methods. At last, the biological functions of representative cell cycle genes for each subtype were analyzed.
RESULTS: Our method showed better and more balanced performance of sensitivity and specificity comparing to other machine learning algorithms. The cell cycle genes had very different expression pattern with non-c...

Source: Combinatorial Chemistry and High Throughput Screening - April 17, 2017 Category: Chemistry Authors: Liu C, Cui P, Huang T Tags: Comb Chem High Throughput Screen Source Type: research