AIMC Topic: Genetic Association Studies

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AI-based diagnosis and phenotype - Genotype correlations in syndromic craniosynostoses.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery Feb 5, 2024
Apert (AS), Crouzon (CS), Muenke (MS), Pfeiffer (PS), and Saethre Chotzen (SCS) are among the most frequently diagnosed syndromic craniosynostoses. The aims of this study were (1) to train an innovative model using artificial intelligence (AI)-based ...
Prospective Studies Retrospective Studies Female Male Humans Artificial Intelligence Phenotype Genetic Association Studies Craniosynostoses Syndrome Photography Infant Child, Preschool Child Genotype
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Molecular Investigation and Preliminary Validation of Candidate Genes Associated with Neurological Damage in Heat Stroke.

Molecular neurobiology Jan 31, 2024
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...
Heat Stroke Protein Interaction Maps Gene Regulatory Networks Genetic Association Studies Computational Biology Signal Transduction Databases, Genetic Gene Ontology Humans HSP90 Heat-Shock Proteins Reproducibility of Results Gene Expression Profiling
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Predicting functional effects of ion channel variants using new phenotypic machine learning methods.

PLoS computational biology Mar 6, 2023
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...
Humans Machine Learning Ion Channels Phenotype Genetic Association Studies Supervised Machine Learning
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Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.

Scientific reports Dec 9, 2021
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...
Humans Algorithms Reproducibility of Results Supervised Machine Learning Mutation, Missense ROC Curve Genetic Association Studies Computational Biology Systems Biology
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Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning.

Human cell Nov 3, 2021
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...
Pancreatitis-Associated Proteins Colitis, Ulcerative Gene Expression Lithostathine alpha-Defensins Humans Machine Learning Genetic Association Studies Computational Biology Logistic Models
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NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases.

Human genetics Aug 26, 2021
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...
Gene Ontology Eye Diseases, Hereditary Ciliopathies Cohort Studies Genetic Association Studies Prospective Studies Molecular Diagnostic Techniques Retrospective Studies Syndrome Humans Mutation Female Genetic Testing Phenotype Male High-Throughput Nucleotide Sequencing Retinal Diseases
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Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Aug 3, 2021
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...
Genetic Association Studies Zea mays Cooking Machine Learning Spectroscopy, Near-Infrared Water Genotype
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Prioritizing and characterizing functionally relevant genes across human tissues.

PLoS computational biology Jul 16, 2021
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...
Protein Interaction Maps Gene Regulatory Networks Genetic Association Studies Computational Biology Models, Genetic Humans Transcription Factors Multigene Family Genome, Human Tissue Distribution Gene Expression Regulation, Developmental Machine Learning Male Neoplasms Transcriptome Software Genome-Wide Association Study Female
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Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.

BMC cardiovascular disorders Jan 28, 2021
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learnin...
Protein Interaction Maps Heart Atria Gene Regulatory Networks Middle Aged Humans Heart Valve Diseases Signal Transduction Genetic Association Studies Gene Expression Profiling Machine Learning Databases, Genetic Oligonucleotide Array Sequence Analysis Proteomics Transcriptome Bayes Theorem Female Case-Control Studies Atrial Fibrillation Male
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DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.

PLoS computational biology Nov 18, 2020
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...
Animals Humans Neural Networks, Computer Deep Learning Phenotype Genetic Predisposition to Disease Genetic Association Studies Computational Biology Databases, Genetic Gene Ontology Loss of Function Mutation
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