AIMC Topic: Genetic Predisposition to Disease

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A deep learning model for prediction of autism status using whole-exome sequencing data.

PLoS computational biology Nov 8, 2024
Autism is a developmental disability. Research demonstrated that children with autism benefit from early diagnosis and early intervention. Genetic factors are considered major contributors to the development of autism. Machine learning (ML), includin...
Humans Neural Networks, Computer Deep Learning Exome Sequencing Multifactorial Inheritance Exome Child Genetic Predisposition to Disease Computational Biology Autistic Disorder
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Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning.

BMC cardiovascular disorders Nov 5, 2024
BACKGROUND: Type II diabetes mellitus (T2DM) is strongly linked with a heightened risk of coronary artery disease (CAD). Exploring biological targets common to T2DM and CAD is essential for CAD intervention strategies.
Humans Machine Learning Gene Regulatory Networks Genetic Predisposition to Disease Computational Biology Databases, Genetic Coronary Artery Disease Myocytes, Cardiac Myocytes, Smooth Muscle Gene Expression Profiling Fibroblast Growth Factor 7 Transcriptome Female Diabetes Mellitus, Type 2 Single-Cell Analysis Aged Male Middle Aged
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Screening the Best Risk Model and Susceptibility SNPs for Chronic Obstructive Pulmonary Disease (COPD) Based on Machine Learning Algorithms.

International journal of chronic obstructive pulmonary disease Nov 5, 2024
BACKGROUND AND PURPOSE: Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors, and genetic factors are important determinants of COPD. This study focuses on scree...
Genetic Association Studies Male Female Humans Logistic Models Case-Control Studies Risk Factors Middle Aged Machine Learning Predictive Value of Tests Aged ROC Curve Risk Assessment Algorithms Pulmonary Disease, Chronic Obstructive Genetic Predisposition to Disease Phenotype Polymorphism, Single Nucleotide Lung
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An interpretable deep learning model for detecting pathogenic variants of breast cancer from hematoxylin and eosin-stained pathological images.

PeerJ Oct 28, 2024
BACKGROUND: Determining the status of breast cancer susceptibility genes () is crucial for guiding breast cancer treatment. Nevertheless, the need for genetic testing among breast cancer patients remains unmet due to high costs and limited resources...
Algorithms Female Adult Breast Neoplasms Humans Eosine Yellowish-(YS) Middle Aged Hematoxylin Deep Learning Genetic Predisposition to Disease Mutation
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Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort.

Clinical nutrition ESPEN Oct 11, 2024
BACKGROUND AND AIM: Carbonated sugar-sweetened beverages (CSSB) intake has been increasingly linked to metabolic diseases. To investigate the association between CSSB intake and metabolic syndrome (MetS) risk, and the interaction between genetic pred...
Adult Male Middle Aged Diet Humans Machine Learning Female Risk Factors Metabolic Syndrome Sugar-Sweetened Beverages Feeding Behavior Carbonated Beverages Gene-Environment Interaction Genome-Wide Association Study Cohort Studies Genetic Predisposition to Disease Polymorphism, Single Nucleotide
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SGLMDA: A Subgraph Learning-Based Method for miRNA-Disease Association Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
MicroRNAs (miRNA) are endogenous non-coding RNAs, typically around 23 nucleotides in length. Many miRNAs have been founded to play crucial roles in gene regulation though post-transcriptional repression in animals. Existing studies suggest that the d...
MicroRNAs Algorithms Neoplasms Genetic Predisposition to Disease Computational Biology Humans Neural Networks, Computer Machine Learning
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Screening COPD-Related Biomarkers and Traditional Chinese Medicine Prediction Based on Bioinformatics and Machine Learning.

International journal of chronic obstructive pulmonary disease Sep 24, 2024
PURPOSE: To employ bioinformatics and machine learning to predict the characteristics of immune cells and genes associated with the inflammatory response and ferroptosis in chronic obstructive pulmonary disease (COPD) patients and to aid in the devel...
Humans Machine Learning Phenotype Biomarkers Pulmonary Disease, Chronic Obstructive Lung Molecular Docking Simulation MicroRNAs Predictive Value of Tests Mendelian Randomization Analysis Drugs, Chinese Herbal Gene Expression Profiling Transcriptome Computational Biology Gene Regulatory Networks Genetic Markers Databases, Genetic Genetic Predisposition to Disease Medicine, Chinese Traditional Ferroptosis
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Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.

Molecular systems biology Sep 16, 2024
Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissues and organs. However, variant effect prediction tools that aim to identify pathogenic variants are typically oblivious to tissue contexts. Here we r...
Genetic Variation Organ Specificity Rare Diseases Machine Learning Genetic Predisposition to Disease Humans Computational Biology
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Screening of genes co-associated with osteoporosis and chronic HBV infection based on bioinformatics analysis and machine learning.

Frontiers in immunology Sep 16, 2024
OBJECTIVE: To identify HBV-related genes (HRGs) implicated in osteoporosis (OP) pathogenesis and develop a diagnostic model for early OP detection in chronic HBV infection (CBI) patients.
Hepatitis B, Chronic Computational Biology Nomograms Support Vector Machine Databases, Genetic Gene Expression Profiling Transcriptome Hepatitis B virus Genetic Predisposition to Disease Humans Machine Learning Osteoporosis
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AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.

Human genomics Sep 11, 2024
Single nucleotide variants (SNVs) can exert substantial and extremely variable impacts on various cellular functions, making accurate predictions of their consequences challenging, albeit crucial especially in clinical settings such as in oncology. L...
Genetic Predisposition to Disease Polymorphism, Single Nucleotide Computational Biology Databases, Genetic Mutation, Missense Artificial Intelligence Software Female Breast Neoplasms Humans
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