AIMC Topic: Genes, Bacterial
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ProClaT, a new bioinformatics tool for in silico protein reclassification: case study of DraB, a protein coded from the draTGB operon in Azospirillum brasilense.
BMC bioinformatics
Dec 15, 2016
BACKGROUND: Azopirillum brasilense is a plant-growth promoting nitrogen-fixing bacteria that is used as bio-fertilizer in agriculture. Since nitrogen fixation has a high-energy demand, the reduction of N to NH by nitrogenase occurs only under limitin...
InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology.
BMC genomics
Aug 31, 2016
BACKGROUND: The Gene Ontology (GO) has been used in high-throughput omics research as a major bioinformatics resource. The hierarchical structure of GO provides users a convenient platform for biological information abstraction and hypothesis testing...
Semi-Supervised Multi-View Learning for Gene Network Reconstruction.
PloS one
Dec 7, 2015
The task of gene regulatory network reconstruction from high-throughput data is receiving increasing attention in recent years. As a consequence, many inference methods for solving this task have been proposed in the literature. It has been recently ...
Genomic language models (gLMs) decode bacterial genomes for improved gene prediction and translation initiation site identification.
Briefings in bioinformatics
Jul 2, 2025
Accurate bacterial gene prediction is essential for understanding microbial functions and advancing biotechnology. Traditional methods based on sequence homology and statistical models often struggle with complex genetic variations and novel sequence...
PLM-ARG: antibiotic resistance gene identification using a pretrained protein language model.
Bioinformatics (Oxford, England)
Nov 1, 2023
MOTIVATION: Antibiotic resistance presents a formidable global challenge to public health and the environment. While considerable endeavors have been dedicated to identify antibiotic resistance genes (ARGs) for assessing the threat of antibiotic resi...
CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.
Nucleic acids research
Jan 6, 2023
The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation a...
Computational prediction and interpretation of both general and specific types of promoters in Escherichia coli by exploiting a stacked ensemble-learning framework.
Briefings in bioinformatics
Mar 22, 2021
Promoters are short consensus sequences of DNA, which are responsible for transcription activation or the repression of all genes. There are many types of promoters in bacteria with important roles in initiating gene transcription. Therefore, solving...
Machine-Learning Classification Suggests That Many Alphaproteobacterial Prophages May Instead Be Gene Transfer Agents.
Genome biology and evolution
Oct 1, 2019
Many of the sequenced bacterial and archaeal genomes encode regions of viral provenance. Yet, not all of these regions encode bona fide viruses. Gene transfer agents (GTAs) are thought to be former viruses that are now maintained in genomes of some b...
Gene essentiality prediction based on fractal features and machine learning.
Molecular bioSystems
Feb 28, 2017
Essential genes are required for the viability of an organism. Accurate and rapid identification of new essential genes is of substantial theoretical interest to synthetic biology and has practical applications in biomedicine. Fractals provide facili...
An integrated machine-learning model to predict prokaryotic essential genes.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2015
Essential genes are indispensable for the target organism's survival. Large-scale identification and characterization of essential genes has shown to be beneficial in both fundamental biology and medicine fields. Current existing genome-scale experim...
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