AIMC Topic: Genes, Essential
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Landscape of essential growth and fluconazole-resistance genes in the human fungal pathogen Cryptococcus neoformans.
PLoS biology
May 22, 2025
Fungi can cause devastating invasive infections, typically in immunocompromised patients. Treatment is complicated both by the evolutionary similarity between humans and fungi and by the frequent emergence of drug resistance. Studies in fungal pathog...
A hybrid machine learning model with attention mechanism and multidimensional multivariate feature coding for essential gene prediction.
BMC biology
Apr 24, 2025
BACKGROUND: Essential genes are crucial for the development, inheritance, and survival of species. The exploration of these genes can unravel the complex mechanisms and fundamental life processes and identify potential therapeutic targets for various...
Machine learning methods for predicting essential metabolic genes from Plasmodium falciparum genome-scale metabolic network.
PloS one
Dec 23, 2024
Essential genes are those whose presence is vital for a cell's survival and growth. Detecting these genes in disease-causing organisms is critical for various biological studies, including understanding microbe metabolism, engineering genetically mod...
Human essential gene identification based on feature fusion and feature screening.
IET systems biology
Nov 22, 2024
Essential genes are necessary to sustain the life of a species under adequate nutritional conditions. These genes have attracted significant attention for their potential as drug targets, especially in developing broad-spectrum antibacterial drugs. H...
HELP: A computational framework for labelling and predicting human common and context-specific essential genes.
PLoS computational biology
Sep 27, 2024
Machine learning-based approaches are particularly suitable for identifying essential genes as they allow the generation of predictive models trained on features from multi-source data. Gene essentiality is neither binary nor static but determined by...
Protein interactions in human pathogens revealed through deep learning.
Nature microbiology
Sep 18, 2024
Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lit...
Differentially used codons among essential genes in bacteria identified by machine learning-based analysis.
Molecular genetics and genomics : MGG
Jul 27, 2024
Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-express...
Robust evaluation of deep learning-based representation methods for survival and gene essentiality prediction on bulk RNA-seq data.
Scientific reports
Jul 24, 2024
Deep learning (DL) has shown potential to provide powerful representations of bulk RNA-seq data in cancer research. However, there is no consensus regarding the impact of design choices of DL approaches on the performance of the learned representatio...
Inference of Essential Genes of the Parasite via Machine Learning.
International journal of molecular sciences
Jun 27, 2024
Over the years, comprehensive explorations of the model organisms (elegant worm) and (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive func...
Essentiality, protein-protein interactions and evolutionary properties are key predictors for identifying cancer-associated genes using machine learning.
Scientific reports
Apr 22, 2024
The distinctive nature of cancer as a disease prompts an exploration of the special characteristics the genes implicated in cancer exhibit. The identification of cancer-associated genes and their characteristics is crucial to further our understandin...
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