AIMC Topic: Genetic Association Studies

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Prioritizing Clinically Relevant Copy Number Variation from Genetic Interactions and Gene Function Data.

PloS one
It is becoming increasingly necessary to develop computerized methods for identifying the few disease-causing variants from hundreds discovered in each individual patient. This problem is especially relevant for Copy Number Variants (CNVs), which can...

Prediction of drug gene associations via ontological profile similarity with application to drug repositioning.

Methods (San Diego, Calif.)
The amount of biomedical literature has been increasing rapidly during the last decade. Text mining techniques can harness this large-scale data, shed light onto complex drug mechanisms, and extract relation information that can support computational...

Exploring the unique characteristics of genes with dual autosomal dominant and recessive inheritance: mechanisms, phenotypes and candidate identification.

Journal of medical genetics
BACKGROUND: Autosomal dominant (AD) inheritance often arises through haploinsufficiency, dominant-negative or gain of function (GoF) effects, while autosomal recessive (AR) inheritance generally results from partial or complete loss of function (LoF)...

Learning genotype-phenotype associations from gaps in multi-species sequence alignments.

Briefings in bioinformatics
Understanding the genetic basis of phenotypic variation is fundamental to biology. Here we introduce GAP, a novel machine learning framework for predicting binary phenotypes from gaps in multi-species sequence alignments. GAP employs a neural network...

Heterogeneous biomedical entity representation learning for gene-disease association prediction.

Briefings in bioinformatics
Understanding the genetic basis of disease is a fundamental aspect of medical research, as genes are the classic units of heredity and play a crucial role in biological function. Identifying associations between genes and diseases is critical for dia...

Discovering genotype-phenotype relationships with machine learning and the Visual Physiology Opsin Database (VPOD).

GigaScience
BACKGROUND: Predicting phenotypes from genetic variation is foundational for fields as diverse as bioengineering and global change biology, highlighting the importance of efficient methods to predict gene functions. Linking genetic changes to phenoty...

Predicting miRNA-disease associations using an ensemble learning framework with resampling method.

Briefings in bioinformatics
MOTIVATION: Accumulating evidences have indicated that microRNA (miRNA) plays a crucial role in the pathogenesis and progression of various complex diseases. Inferring disease-associated miRNAs is significant to explore the etiology, diagnosis and tr...

Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.

Methods in molecular biology (Clifton, N.J.)
To develop medical treatments and prevention, the association between disease and genetic variants needs to be identified. The main goal of genome-wide association study (GWAS) is to discover the underlying reason for vulnerability to disease and uti...