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Genetic Association Studies

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ES-MDA: Enhanced Similarity-based MiRNA-Disease Association.

Current protein & peptide science
Accumulating evidence demonstrate that miRNAs can be treated as critical biomarkers in various complex human diseases. Thus, the identifications on potential miRNA-disease associations have become a hotpot for providing better understanding of diseas...

Construction of gene-classifier and co-expression network analysis of genes in association with major depressive disorder.

Psychiatry research
Because the pathogenesis of major depressive disorder (MDD) is still unclear and the accurate diagnosis remains unavailable, we aimed to analyze its molecular mechanisms and develop a gene classifier to improve diagnostic accuracy. We extracted diffe...

Correlations Between Phenotypes and Biological Process Ontologies in Monogenic Human Diseases.

Interdisciplinary sciences, computational life sciences
A substantial body of research is focused to improve the understanding of the relationship between genotypes and phenotypes. Genotype-phenotype studies have shown promise in improving disease diagnosis in humans and identification of specific clinica...

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.

PLoS computational biology
Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted...

Machine learning demonstrates that somatic mutations imprint invariant morphologic features in myelodysplastic syndromes.

Blood
Morphologic interpretation is the standard in diagnosing myelodysplastic syndrome (MDS), but it has limitations, such as varying reliability in pathologic evaluation and lack of integration with genetic data. Somatic events shape morphologic features...

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...

Prioritizing and characterizing functionally relevant genes across human tissues.

PLoS computational biology
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combini...

NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases.

Human genetics
Syndromic retinal diseases (SRDs) are a group of complex inherited systemic disorders, with challenging molecular underpinnings and clinical management. Our main goal is to improve clinical and molecular SRDs diagnosis, by applying a structured pheno...

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is strongly modulated by the environment, and has a complex genetic architecture. Lack of high-throughpu...