AIMC Topic: Polymorphism, Single Nucleotide

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Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model.

IEEE transactions on bio-medical engineering Apr 9, 2018
Brain-wide and genome-wide association (BW-GWA) study is presented in this paper to identify the associations between the brain imaging phenotypes (i.e., regional volumetric measures) and the genetic variants [i.e., single nucleotide polymorphism (SN...
Genome-Wide Association Study Polymorphism, Single Nucleotide Computational Biology Magnetic Resonance Imaging Regression Analysis Alzheimer Disease Humans Machine Learning Databases, Factual Brain
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Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Transcriptome Case-Control Studies Adolescent Human Growth Hormone Growth Disorders Female Humans Male Machine Learning Severity of Illness Index Biomarkers Gene Expression Profiling Polymorphism, Single Nucleotide Child, Preschool Predictive Value of Tests Child Principal Component Analysis ROC Curve Healthy Volunteers Gene Regulatory Networks Datasets as Topic
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Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation.

PloS one Apr 5, 2018
The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (L...
Male Kidney Transplantation Humans ATP Binding Cassette Transporter, Subfamily B Middle Aged Computational Biology Neural Networks, Computer Female Adolescent Tacrolimus Polymorphism, Single Nucleotide Young Adult Biological Availability Genotype Adult Cytochrome P-450 CYP3A
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Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research Mar 27, 2018
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...
Gene Expression Profiling Genomics Polymorphism, Single Nucleotide Computational Biology Epigenomics Humans Neural Networks, Computer Machine Learning Animals Regulatory Sequences, Nucleic Acid Models, Genetic Gene Expression Regulation Promoter Regions, Genetic Chromosomes
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Generalising better: Applying deep learning to integrate deleteriousness prediction scores for whole-exome SNV studies.

PloS one Mar 14, 2018
Many automatic classifiers were introduced to aid inference of phenotypical effects of uncategorised nsSNVs (nonsynonymous Single Nucleotide Variations) in theoretical and medical applications. Lately, several meta-estimators have been proposed that ...
Internet Exome Machine Learning Polymorphism, Single Nucleotide Models, Genetic Sequence Analysis, DNA
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GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Journal of psychiatric research Feb 2, 2018
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be ...
Polymorphism, Single Nucleotide Support Vector Machine Outcome Assessment, Health Care Duloxetine Hydrochloride Serotonin and Noradrenaline Reuptake Inhibitors Male Middle Aged Depressive Disorder, Major Genome-Wide Association Study Humans Prognosis Female Adult Sensitivity and Specificity
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Interaction of Vitamin E Intake and Pro12Ala Polymorphism of PPARG with Adiponectin Levels.

Journal of nutrigenetics and nutrigenomics Feb 2, 2018
BACKGROUND/AIM: One of the beneficial effects associated with vitamin E intake is the enhancement of peroxisome proliferator-activated receptor gamma (PPARĪ³) activity and the consequent upregulation of adiponectin expression. The aim of this study wa...
Polymorphism, Single Nucleotide Nutrigenomics Cross-Sectional Studies Humans Genotype PPAR gamma Male Adiponectin Middle Aged Vitamin E Amino Acid Substitution Female Adolescent Young Adult Adult
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Machine Learning on a Genome-wide Association Study to Predict Late Genitourinary Toxicity After Prostate Radiation Therapy.

International journal of radiation oncology, biology, physics Jan 31, 2018
PURPOSE: Late genitourinary (GU) toxicity after radiation therapy limits the quality of life of prostate cancer survivors; however, efforts to explain GU toxicity using patient and dose information have remained unsuccessful. We identified patients w...
Regression Analysis Predictive Value of Tests Area Under Curve Prostatic Neoplasms Androgen Antagonists Confidence Intervals Genotyping Techniques Brachytherapy Urination Disorders Reproducibility of Results Male Quality of Life Genome-Wide Association Study Polymorphism, Single Nucleotide Humans Machine Learning Symptom Assessment Risk Urogenital System Lower Urinary Tract Symptoms Nocturia Urinary Retention Urination
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Prediction of opioid dose in cancer pain patients using genetic profiling: not yet an option with support vector machine learning.

BMC research notes Jan 27, 2018
OBJECTIVE: Use of opioids for pain management has increased over the past decade; however, inadequate analgesic response is common. Genetic variability may be related to opioid efficacy, but due to the many possible combinations and variables, statis...
Receptors, Opioid, delta Aged Male Gene Frequency Middle Aged Genotype Humans Cancer Pain Polymorphism, Single Nucleotide Support Vector Machine Female Receptors, Opioid, mu Dose-Response Relationship, Drug Catechol O-Methyltransferase Analgesics, Opioid Morphine
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Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Proceedings of the National Academy of Sciences of the United States of America Jan 22, 2018
Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to ca...
Polymorphism, Single Nucleotide Probability Genome, Human Humans Life Style Machine Learning Neoplasms Genetic Predisposition to Disease
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