AI Medical Compendium Topic

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Databases, Genetic

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A knowledge-based approach for predicting gene-disease associations.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances of next-generation sequence technologies have made it possible to rapidly and inexpensively identify gene variations. Knowing the disease association of these gene variations is important for early intervention to treat de...

Tracking medical genetic literature through machine learning.

Molecular genetics and metabolism
There has been remarkable progress in identifying the causes of genetic conditions as well as understanding how changes in specific genes cause disease. Though difficult (and often superficial) to parse, an interesting tension involves emphasis on ba...

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

PloS one
Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Co...

DiscMLA: An Efficient Discriminative Motif Learning Algorithm over High-Throughput Datasets.

IEEE/ACM transactions on computational biology and bioinformatics
The transcription factors (TFs) can activate or suppress gene expression by binding to specific sites, hence are crucial regulatory elements for transcription. Recently, series of discriminative motif finders have been tailored to offering promising ...

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update.

Nucleic acids research
Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gen...

DiMeX: A Text Mining System for Mutation-Disease Association Extraction.

PloS one
The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gather such mutation-disease associations into public knowledge bases, but manual curation slows down th...

Extending gene ontology in the context of extracellular RNA and vesicle communication.

Journal of biomedical semantics
BACKGROUND: To address the lack of standard terminology to describe extracellular RNA (exRNA) data/metadata, we have launched an inter-community effort to extend the Gene Ontology (GO) with subcellular structure concepts relevant to the exRNA domain....

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

Journal of theoretical biology
Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algor...

The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database.

Database : the journal of biological databases and curation
The Rat Genome Database (RGD;http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a...

GO annotation in InterPro: why stability does not indicate accuracy in a sea of changing annotations.

Database : the journal of biological databases and curation
The removal of annotation from biological databases is often perceived as an indicator of erroneous annotation. As a corollary, annotation stability is considered to be a measure of reliability. However, diverse data-driven events can affect the stab...