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Genetic Association Studies

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Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning.

Human cell
Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC. However, it still lacks specific diagnostic signatures. The aim of our study was to explore effici...

Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.

Scientific reports
Among an assortment of genetic variations, Missense are major ones which a small subset of them may led to the upset of the protein function and ultimately end in human diseases. Various machine learning methods were declared to differentiate deleter...

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...

Predicting functional effects of ion channel variants using new phenotypic machine learning methods.

PLoS computational biology
Missense variants in genes encoding ion channels are associated with a spectrum of severe diseases. Variant effects on biophysical function correlate with clinical features and can be categorized as gain- or loss-of-function. This information enables...

Molecular Investigation and Preliminary Validation of Candidate Genes Associated with Neurological Damage in Heat Stroke.

Molecular neurobiology
Heat stroke (HS) is a severe medical condition characterized by a systemic inflammatory response that may precipitate multi-organ dysfunction, with a particular predilection for inducing profound central nervous system impairments. We aim to employ b...

PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies.

Genome medicine
Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interpre...

A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation.

BMC bioinformatics
BACKGROUND: The exploration of gene-disease associations is crucial for understanding the mechanisms underlying disease onset and progression, with significant implications for prevention and treatment strategies. Advances in high-throughput biotechn...

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...