AIMC Topic: Genotype

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Differential gene expression and gene ontologies associated with increasing water-stress in leaf and root transcriptomes of perennial ryegrass (Lolium perenne).

PloS one Jul 30, 2019
Perennial ryegrass (Lolium perenne) is a forage and amenity grass species widely cultivated in temperate regions worldwide. As such, perennial ryegrass populations are exposed to a range of environmental conditions and stresses on a seasonal basis an...
Gene Expression Regulation, Plant Droughts Lolium Gene Expression Profiling Transcriptome Genotype Plant Leaves Plant Roots Dehydration Plant Proteins Gene Ontology
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.

Scientific reports Jul 17, 2019
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machin...
Area Under Curve Crohn Disease Neural Networks, Computer Alleles Nonlinear Dynamics Female Genotype Male Genome-Wide Association Study Humans Logistic Models Genotyping Techniques Deep Learning ROC Curve Models, Genetic INDEL Mutation Decision Trees Genetic Predisposition to Disease Polymorphism, Single Nucleotide
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Machine and deep learning meet genome-scale metabolic modeling.

PLoS computational biology Jul 11, 2019
Omic data analysis is steadily growing as a driver of basic and applied molecular biology research. Core to the interpretation of complex and heterogeneous biological phenotypes are computational approaches in the fields of statistics and machine lea...
Deep Learning Genotype Computational Biology Metabolic Networks and Pathways Genome Machine Learning Phenotype
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New Deep Learning Genomic-Based Prediction Model for Multiple Traits with Binary, Ordinal, and Continuous Phenotypes.

G3 (Bethesda, Md.) May 7, 2019
Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between traits with mixed phenotypes...
Reproducibility of Results Deep Learning Genomics Genotype Algorithms Phenotype Genome, Plant Quantitative Trait, Heritable Genetic Association Studies Plant Breeding Models, Genetic Selection, Genetic Genome
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Contemporary pharmacogenetic assays in view of the PharmGKB database.

Pharmacogenomics Mar 18, 2019
AIM: Six modern PGx assays were compared with the Pharmacogenomics Knowledge Base (PharmGKB) to determine the proportion of the currently known PGx genotypes that are assessed by these assays.
Genotype Knowledge Bases Humans Pharmacogenomic Testing Databases, Factual Pharmacogenetics
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A multi-task convolutional deep neural network for variant calling in single molecule sequencing.

Nature communications Mar 1, 2019
The accurate identification of DNA sequence variants is an important, but challenging task in genomics. It is particularly difficult for single molecule sequencing, which has a per-nucleotide error rate of ~5-15%. Meeting this demand, we developed Cl...
DNA Mutational Analysis Base Sequence Genome, Human Genotyping Techniques Polymorphism, Single Nucleotide Genotype Computational Biology Sequence Analysis, DNA INDEL Mutation Nanopores Humans Neural Networks, Computer Software Genome-Wide Association Study Genomics
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Severe Dengue Prognosis Using Human Genome Data and Machine Learning.

IEEE transactions on bio-medical engineering Feb 4, 2019
UNLABELLED: Dengue has become one of the most important worldwide arthropod-borne diseases. Dengue phenotypes are based on laboratorial and clinical exams, which are known to be inaccurate.
Severe Dengue Humans Polymorphism, Single Nucleotide Machine Learning Genotype Sensitivity and Specificity Phenotype Predictive Value of Tests Brazil Prognosis Genome, Human Case-Control Studies
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Radiomics-based machine learning methods for isocitrate dehydrogenase genotype prediction of diffuse gliomas.

Journal of cancer research and clinical oncology Feb 4, 2019
PURPOSE: Reliable and accurate predictive models are necessary to drive the success of radiomics. Our aim was to identify the optimal radiomics-based machine learning method for isocitrate dehydrogenase (IDH) genotype prediction in diffuse gliomas.
Humans Machine Learning Female Aged Aged, 80 and over Young Adult Image Interpretation, Computer-Assisted Isocitrate Dehydrogenase Adolescent Adult Genotype Brain Neoplasms Glioma Male Magnetic Resonance Imaging Middle Aged
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Xrare: a machine learning method jointly modeling phenotypes and genetic evidence for rare disease diagnosis.

Genetics in medicine : official journal of the American College of Medical Genetics Jan 24, 2019
PURPOSE: Despite the successful progress next-generation sequencing technologies has achieved in diagnosing the genetic cause of rare Mendelian diseases, the current diagnostic rate is still far from satisfactory because of heterogeneity, imprecision...
Genetic Variation Humans High-Throughput Nucleotide Sequencing Machine Learning Genotype Rare Diseases Computational Biology Software Exome Mutation Phenotype Genetic Testing Genomics
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A single nucleotide polymorphism panel for individual identification and ancestry assignment in Caucasians and four East and Southeast Asian populations using a machine learning classifier.

Forensic science, medicine, and pathology Jan 16, 2019
Single nucleotide polymorphism (SNP) profiling is an effective means of individual identification and ancestry inferences in forensic genetics. This study established a SNP panel for the simultaneous individual identification and ancestry assignment ...
Chromosomes, Human, X DNA Degradation, Necrotic Asia Chromosomes, Human, Y Genetics, Population Male DNA Fingerprinting Polymorphism, Single Nucleotide DNA, Mitochondrial Humans Genotype Asian People Machine Learning Support Vector Machine White People Retrospective Studies Gene Frequency Female
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