AIMC Topic: Phenotype

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OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

Bioinformatics (Oxford, England)
MOTIVATION: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task.

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype.

BioMed research international
Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic vari...

A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases.

Journal of biomedical informatics
Automated phenotype identification plays a critical role in cohort selection and bioinformatics data mining. Natural Language Processing (NLP)-informed classification techniques can robustly identify phenotypes in unstructured medical notes. In this ...

Multivariate Quantitative Multifactor Dimensionality Reduction for Detecting Gene-Gene Interactions.

Human heredity
OBJECTIVES: To determine gene-gene interactions and missing heritability of complex diseases is a challenging topic in genome-wide association studies. The multifactor dimensionality reduction (MDR) method is one of the most commonly used methods for...

A Robust e-Epidemiology Tool in Phenotyping Heart Failure with Differentiation for Preserved and Reduced Ejection Fraction: the Electronic Medical Records and Genomics (eMERGE) Network.

Journal of cardiovascular translational research
Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burden of this disease. The use of electronic medical record (EMR) data for this purpose is challenging g...

Computer-Assisted Transgenesis of Caenorhabditis elegans for Deep Phenotyping.

Genetics
A major goal in the study of human diseases is to assign functions to genes or genetic variants. The model organism Caenorhabditis elegans provides a powerful tool because homologs of many human genes are identifiable, and large collections of geneti...

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease.

American journal of human genetics
The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been ava...

Artificial neural networks reveal efficiency in genetic value prediction.

Genetics and molecular research : GMR
The objective of this study was to evaluate the efficiency of artificial neural networks (ANNs) for predicting genetic value in experiments carried out in randomized blocks. Sixteen scenarios were simulated with different values of heritability (10, ...

Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

BMC medical informatics and decision making
BACKGROUND: Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mini...