DeeplyEssential: a deep neural network for predicting essential genes in microbes.

ABSTRACT:

Background

Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provide targets for the design of novel antibiotic compounds or antimicrobial strategies.

Results

We propose a deep neural network for predicting essential genes in microbes. Our architecture called DEEPLYESSENTIAL makes minimal assumptions about the input data (i.e., it only uses gene primary sequence and the corresponding protein sequence) to carry out the prediction thus maximizing its practical application compared to existing predictors that require structural or topological features which might not be readily available. We also expose and study a hidden performance bias that effected previous classifiers. Extensive results show

SUBMITTER: Hasan MA 

PROVIDER: S-EPMC7525945 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature