AI Medical Compendium Topic:
Databases, Genetic

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HyDRA: gene prioritization via hybrid distance-score rank aggregation.

Bioinformatics (Oxford, England)
UNLABELLED: Gene prioritization refers to a family of computational techniques for inferring disease genes through a set of training genes and carefully chosen similarity criteria. Test genes are scored based on their average similarity to the traini...

DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis.

Bioinformatics (Oxford, England)
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...

How to learn about gene function: text-mining or ontologies?

Methods (San Diego, Calif.)
As the amount of genome information increases rapidly, there is a correspondingly greater need for methods that provide accurate and automated annotation of gene function. For example, many high-throughput technologies--e.g., next-generation sequenci...

Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data.

Computers in biology and medicine
This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering app...

The limitations of simple gene set enrichment analysis assuming gene independence.

Statistical methods in medical research
Since its first publication in 2003, the Gene Set Enrichment Analysis method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess en...

argNorm: normalization of antibiotic resistance gene annotations to the Antibiotic Resistance Ontology (ARO).

Bioinformatics (Oxford, England)
SUMMARY: Currently available and frequently used tools for annotating antibiotic resistance genes (ARGs) in genomes and metagenomes provide results using inconsistent nomenclature. This makes the comparison of different ARG annotation outputs challen...

Post-composing ontology terms for efficient phenotyping in plant breeding.

Database : the journal of biological databases and curation
Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on...

A graph neural network approach for accurate prediction of pathogenicity in multi-type variants.

Briefings in bioinformatics
Accurate prediction of pathogenic variants in human disease-associated genes would have a profound effect on clinical decision-making; however, it remains a significant challenge due to the overwhelming number of these variants. We propose graph neur...

DOMSCNet: a deep learning model for the classification of stomach cancer using multi-layer omics data.

Briefings in bioinformatics
The rapid advancement of next-generation sequencing (NGS) technology and the expanding availability of NGS datasets have led to a significant surge in biomedical research. To better understand the molecular processes, underlying cancer and to support...

AskBeacon-performing genomic data exchange and analytics with natural language.

Bioinformatics (Oxford, England)
MOTIVATION: Enabling clinicians and researchers to directly interact with global genomic data resources by removing technological barriers is vital for medical genomics. AskBeacon enables large language models (LLMs) to be applied to securely shared ...