Bacterial classification with convolutional neural networks based on different data reduction layers.

Bacterial classification with convolutional neural networks based on different data reduction layers.
Nucleosides Nucleotides Nucleic Acids. 2019 Aug 16;:1-11
Authors: Abd-Alhalem SM, Soliman NF, Eldin S, Abd Elrahman SE, Ismail NA, El-Rabaie EM, El-Samie FEA
Abstract
For high accuracy classification of DNA sequences through Convolutional Neural Networks (CNNs), it is essential to use an efficient sequence representation that can accelerate similarity comparison between DNA sequences. In addition, CNN networks can be improved by avoiding the dimensionality problem associated with multi-layer CNN features. This paper presents a new approach for classification of bacterial DNA sequences based on a custom layer. A CNN is used with Frequency Chaos Game Representation (FCGR) of DNA. The FCGR is adopted as a sequence representation method with a suitable choice of the frequency k-lengthen words occurrence in DNA sequences. The DNA sequence is mapped using FCGR that produces an image of a gene sequence. This sequence displays both local and global patterns. A pre-trained CNN is built for image classification. First, the image is converted to feature maps through convolutional layers. This is sometimes followed by a down-sampling operation that reduces the spatial size of the feature map and removes redundant spatial information using the pooling layers. The Random Projection (RP) with an activation function, which carries data with a decent...

Source: Nucleosides, Nucleotides and Nucleic Acids - August 18, 2019 Category: Biochemistry Tags: Nucleosides Nucleotides Nucleic Acids Source Type: research