Investigating ensemble methods for essential gene predictions in bacteria - Patel, Vanisha (2022)
Essential genes are the genes required for an organism to survive in stable conditions with an abundance of nutrients. The identification of essential genes is important to both our understanding of bacterial organisms and our ability to manipulate them. Many machine learning methods have been proposed for the prediction of essential genes. However, the majority of these studies have a limited focus, i.e. a single optimised classifier and feature set combination to predict genes within the same organism. Therefore, as the models have a narrow scope they cannot be reliably applied to newly sequenced organisms. This ability of a model to generalise to new data can be improved by increasing the dataset and combining results from different classifiers.