AIMC Topic: Genome-Wide Association Study
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Screening of Secretory Proteins Linking Major Depressive Disorder with Heart Failure Based on Comprehensive Bioinformatics Analysis and Machine Learning.
Biomolecules
Jul 4, 2024
BACKGROUND: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD's involvement in HF pathogenesis and identify candidate biomarkers fo...
Characterizing mitochondrial features in osteoarthritis through integrative multi-omics and machine learning analysis.
Frontiers in immunology
Jul 4, 2024
PURPOSE: Osteoarthritis (OA) stands as the most prevalent joint disorder. Mitochondrial dysfunction has been linked to the pathogenesis of OA. The main goal of this study is to uncover the pivotal role of mitochondria in the mechanisms driving OA dev...
Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to .
International journal of molecular sciences
Jun 25, 2024
(Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor gene...
Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.
Nature genetics
Jun 11, 2024
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disea...
Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach.
International immunopharmacology
Jun 8, 2024
OBJECTIVES: This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury (AKI), including sepsis-associated AKI (SA-AKI), a frequent complication in critically ill sepsis patients.
Prediction of adverse drug reactions due to genetic predisposition using deep neural networks.
Molecular informatics
Jun 8, 2024
Drug development is a long and costly process, often limited by the toxicity and adverse drug reactions (ADRs) caused by drug candidates. Even on the market, some drugs can cause strong ADRs that can vary depending on an individual polymorphism. The ...
TSVM: Transfer Support Vector Machine for Predicting MPRA Validated Regulatory Variants.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2024
Genome-wide association studies have shown that common genetic variants associated with complex diseases are mostly located in non-coding regions, which may not be causal. In addition, the limited number of validated non-coding functional variants ma...
Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.
NPJ systems biology and applications
May 30, 2024
Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor's (TF) binding strength, affect enhancer's chromatin activity or interaction, and eventually chang...
Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.
Scientific reports
May 30, 2024
We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baselin...
Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.
Genes
May 26, 2024
Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increa...
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