AIMC Topic: Multigene Family
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Novel symmetry-based gene-gene dissimilarity measures utilizing Gene Ontology: Application in gene clustering.
Gene
Sep 2, 2018
In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorith...
Multi-Factored Gene-Gene Proximity Measures Exploiting Biological Knowledge Extracted from Gene Ontology: Application in Gene Clustering.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 21, 2018
To describe the cellular functions of proteins and genes, a potential dynamic vocabulary is Gene Ontology (GO), which comprises of three sub-ontologies namely, Biological-process, Cellular-component, and Molecular-function. It has several application...
Genome-Wide Detection and Analysis of Multifunctional Genes.
PLoS computational biology
Oct 5, 2015
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular...
IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.
mBio
Jul 14, 2015
UNLABELLED: In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In...
Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.
BMC bioinformatics
Feb 14, 2015
BACKGROUND: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the li...
DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis.
Bioinformatics (Oxford, England)
Oct 17, 2014
SUMMARY: Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computati...
Predicting Biological Activity from Biosynthetic Gene Clusters Using Neural Networks.
Journal of chemical information and modeling
Jul 14, 2025
Microorganisms such as bacteria and fungi have been used for natural products that translate to drugs. However, assessing the bioactivity of extract from culture to identify novel natural molecules remains a strenuous process due to the cumbersome or...
Discovery of naturally inspired antimicrobial peptides using deep learning.
Bioorganic chemistry
Jun 15, 2025
Non-ribosomal peptides (NRPs) are promising lead compounds for novel antibiotics. Bioinformatic mining of silent microbial NRPS gene clusters provide crucial insights for the discovery and de novo design of bioactive peptides. Here, we describe the e...
Deciphering the biosynthetic potential of microbial genomes using a BGC language processing neural network model.
Nucleic acids research
Apr 10, 2025
Biosynthetic gene clusters (BGCs), key in synthesizing microbial secondary metabolites, are mostly hidden in microbial genomes and metagenomes. To unearth this vast potential, we present BGC-Prophet, a transformer-based language model for BGC predict...
DeepES: deep learning-based enzyme screening to identify orphan enzyme genes.
Bioinformatics (Oxford, England)
Mar 4, 2025
MOTIVATION: Progress in sequencing technology has led to determination of large numbers of protein sequences, and large enzyme databases are now available. Although many computational tools for enzyme annotation were developed, sequence information i...
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