A review on convolutional neural network based deep learning methods in gene expression data for disease diagnosis

Bioinformatics is the discipline of employing informatics technologies on biological datasets to extract the hidden knowledge from both biology and computer science fields. Gene expression datasets are widely used in disease prediction and diagnosis especially in cancer treatment. There are many computational techniques that are available for gene expression analysis. Deep learning methods are a fragment of machine learning techniques which are based on artificial neural networks. Convolutional neural networks are the most important deep learning model that is designed for data that comes in the form of multidimensional arrays. This paper reviews the recent research works that utilize convolutional neural network deep learning methods on gene expression data analysis. (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Advances in Materials Research-2019.