AIMC Topic: Phenotype

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Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

PLoS computational biology Aug 14, 2020
Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the re...
Adipocytes Cell Size Middle Aged Genome-Wide Association Study Polymorphism, Single Nucleotide Computational Biology Body Mass Index Obesity Adipose Tissue Phenotype Female Adult Male Humans Neural Networks, Computer Machine Learning
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Chances and challenges of machine learning-based disease classification in genetic association studies illustrated on age-related macular degeneration.

Genetic epidemiology Aug 2, 2020
Imaging technology and machine learning algorithms for disease classification set the stage for high-throughput phenotyping and promising new avenues for genome-wide association studies (GWAS). Despite emerging algorithms, there has been no successfu...
Machine Learning Algorithms Phenotype Diagnostic Errors Humans Macular Degeneration United Kingdom Likelihood Functions High-Temperature Requirement A Serine Peptidase 1 Genome-Wide Association Study Models, Genetic Proteins
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Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men.

Calcified tissue international Jul 29, 2020
The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Stud...
Fractures, Bone Humans Activities of Daily Living Machine Learning Phenotype Bone Density Male Aged Risk Assessment Aged, 80 and over Cohort Studies Genomics
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COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda.

Respiratory medicine Jul 28, 2020
Chronic Obstructive Pulmonary Disease (COPD) is a highly heterogeneous condition projected to become the third leading cause of death worldwide by 2030. To better characterize this condition, clinicians have classified patients sharing certain sympto...
Humans Cluster Analysis Pulmonary Disease, Chronic Obstructive Machine Learning Algorithms Comorbidity Genomics Phenotype Biomarkers Research
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An enhanced machine learning tool for cis-eQTL mapping with regularization and confounder adjustments.

Genetic epidemiology Jul 22, 2020
Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. However, these eQTL studies may suffer from low or moderate statistical power and overly conservative fal...
Polymorphism, Single Nucleotide Genotype Models, Genetic Gene Expression Regulation Quantitative Trait Loci Confounding Factors, Epidemiologic Machine Learning Algorithms Phenotype Gene Expression Profiling Humans
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Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

Gut Jul 20, 2020
OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), hi...
Humans Consensus Biomarkers, Tumor Neoplasm Grading Gene Expression Regulation, Neoplastic Phenotype Disease Progression Biopsy Predictive Value of Tests Gene Expression Profiling Prognosis RNA Deep Learning Colorectal Neoplasms Datasets as Topic
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Opportunities and challenges in the collection and analysis of digital phenotyping data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Jul 17, 2020
The broad adoption and use of smartphones has led to fundamentally new opportunities for capturing social, behavioral, and cognitive phenotypes in free-living settings, outside of research laboratories and clinics. Predicated on the use of existing p...
Smartphone Data Collection Machine Learning Research Design Phenotype
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Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping.

Nature communications Jul 15, 2020
Predicting effects of gene regulatory elements (GREs) is a longstanding challenge in biology. Machine learning may address this, but requires large datasets linking GREs to their quantitative function. However, experimental methods to generate such d...
Regulatory Sequences, Nucleic Acid Computational Biology Gene Knockout Techniques Escherichia coli Genome, Bacterial Sequence Analysis, DNA Ribosomes High-Throughput Nucleotide Sequencing Datasets as Topic Molecular Sequence Annotation Binding Sites Phenotype Deep Learning
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Identification of Patients with Heart Failure in Large Datasets.

Heart failure clinics Jul 9, 2020
Large registries, administrative data, and the electronic health record (EHR) offer opportunities to identify patients with heart failure, which can be used for research purposes, process improvement, and optimal care delivery. Identification of case...
Heart Failure Electronic Health Records Global Health Registries Humans Morbidity Machine Learning Phenotype
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Morphological traits of drought tolerant horse gram germplasm: classification through machine learning.

Journal of the science of food and agriculture Jul 3, 2020
BACKGROUND: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are...
Machine Learning Algorithms Phenotype Stress, Physiological Quantitative Trait Loci Droughts Plant Breeding Genotype Seeds Fabaceae
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