AIMC Topic: Phenotype

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Correlations Between Phenotypes and Biological Process Ontologies in Monogenic Human Diseases.

Interdisciplinary sciences, computational life sciences Oct 28, 2020
A substantial body of research is focused to improve the understanding of the relationship between genotypes and phenotypes. Genotype-phenotype studies have shown promise in improving disease diagnosis in humans and identification of specific clinica...
Databases, Genetic Biological Ontologies Gene Ontology Humans Phenotype Genetic Association Studies
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Application of ensemble learning to genomic selection in chinese simmental beef cattle.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie Oct 22, 2020
Genomic selection (GS) using the whole-genome molecular makers to predict genomic estimated breeding values (GEBVs) is revolutionizing the livestock and plant breeding. Seeking out novel strategies with higher prediction accuracy for GS has been the ...
Phenotype Cattle Reproducibility of Results Machine Learning Animals Genomics China Genotype
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Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning.

Scientific reports Oct 20, 2020
For centuries humans have been fascinated by the natural beauty of horses in motion and their different gaits. Gait classification (GC) is commonly performed through visual assessment and reliable, automated methods for real-time objective GC in hors...
Automation Horses Lameness, Animal Animals Algorithms Image Processing, Computer-Assisted Gait Phenotype Motion Computer Simulation Biomechanical Phenomena Machine Learning
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Predicting antimicrobial resistance using conserved genes.

PLoS computational biology Oct 19, 2020
A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features de...
Algorithms Anti-Bacterial Agents Drug Resistance, Bacterial Phenotype Genomics Bacteria Genome, Bacterial Machine Learning Conserved Sequence
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Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Oct 15, 2020
INTRODUCTION: Nontraumatic intracranial hemorrhage (ICH) is a neurological emergency of research interest; however, unlike ischemic stroke, has not been well studied in large datasets due to the lack of an established administrative claims-based defi...
Support Vector Machine Predictive Value of Tests Data Mining Intracranial Hemorrhages International Classification of Diseases Health Services Research Administrative Claims, Healthcare Aged Aged, 80 and over Humans Male Phenotype Middle Aged Female Reproducibility of Results
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SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning.

Scientific reports Oct 15, 2020
Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we presen...
Staining and Labeling Pancreatic Neoplasms Microscopy, Fluorescence Coloring Agents Actins Keratins Biomarkers, Tumor Middle Aged Deep Learning Image Processing, Computer-Assisted Algorithms Phenotype Female Aged Humans
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How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

International journal of molecular sciences Oct 12, 2020
The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F population were genotype...
Waxes Quantitative Trait Loci Genes, Plant Chromosome Mapping Biomarkers Genotype Genetic Markers Secale Genetics, Population Machine Learning Phenotype
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Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Clinical journal of the American Society of Nephrology : CJASN Oct 8, 2020
BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.
Prognosis Acute Kidney Injury Electronic Health Records Female Humans Phenotype Databases, Factual Simplified Acute Physiology Score Glutamyl Aminopeptidase Creatinine L-Lactate Dehydrogenase Alanine Transaminase Bilirubin Lactic Acid Liver Diseases Blood Urea Nitrogen Leukocyte Count Deep Learning Aged Sepsis Male Renal Dialysis Middle Aged United States Comorbidity
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Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Journal of human genetics Oct 2, 2020
Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A de...
Algorithms Phenotype Female Risk Factors Humans Neural Networks, Computer ROC Curve Genetic Predisposition to Disease Polymorphism, Single Nucleotide Multifactorial Inheritance Breast Neoplasms Biomarkers, Tumor Case-Control Studies Genome-Wide Association Study
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Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning.

Gut Sep 30, 2020
OBJECTIVE: Tumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic i...
Deep Learning Female Survival Analysis Humans Liver Neoplasms Aged Phenotype Carcinoma, Hepatocellular Male Prognosis Neoplasm Staging Middle Aged
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