AIMC Topic: Phenotype

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FlyVISTA, an integrated machine learning platform for deep phenotyping of sleep in .

Science advances Mar 12, 2025
There is great interest in using genetically tractable organisms such as to gain insights into the regulation and function of sleep. However, sleep phenotyping in has largely relied on simple measures of locomotor inactivity. Here, we present FlyVI...
Drosophila melanogaster Drosophila Deep Learning Machine Learning Sleep Phenotype Behavior, Animal Animals
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Improving genetic variant identification for quantitative traits using ensemble learning-based approaches.

BMC genomics Mar 12, 2025
BACKGROUND: Genome-wide association studies (GWAS) are rapidly advancing due to the improved resolution and completeness provided by Telomere-to-Telomere (T2T) and pangenome assemblies. While recent advancements in GWAS methods have primarily focused...
Quantitative Trait Loci Genome-Wide Association Study Humans Polymorphism, Single Nucleotide Ensemble Learning Machine Learning Genetic Variation Quantitative Trait, Heritable Phenotype
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Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration.

Nature communications Mar 12, 2025
Predicting and quantifying phenotypic consequences of genetic variants in rare disorders is a major challenge, particularly pertinent for 'actionable' genes such as thyroid hormone transporter MCT8 (encoded by the X-linked SLC16A2 gene), where loss-o...
Thyroid Hormones Loss of Function Mutation Muscular Atrophy Male Deep Learning Genomics X-Linked Intellectual Disability Muscle Hypotonia Humans Monocarboxylic Acid Transporters Phenotype Symporters Female
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Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease.

Genome biology Mar 10, 2025
BACKGROUND: Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been limited by phenotyping challenges and ...
Machine Learning Genetic Predisposition to Disease Humans Phenotype Case-Control Studies Polymorphism, Single Nucleotide Male Female Genome-Wide Association Study Fatty Liver Middle Aged
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Genomic selection in pig breeding: comparative analysis of machine learning algorithms.

Genetics, selection, evolution : GSE Mar 10, 2025
BACKGROUND: The effectiveness of genomic prediction (GP) significantly influences breeding progress, and employing SNP markers to predict phenotypic values is a pivotal aspect of pig breeding. Machine learning (ML) methods are usually used to predict...
Animals Swine Genomics Machine Learning Breeding Polymorphism, Single Nucleotide Algorithms Selection, Genetic Models, Genetic Phenotype
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Enhancing Bacterial Phenotype Classification Through the Integration of Autogating and Automated Machine Learning in Flow Cytometric Analysis.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Mar 10, 2025
Although flow cytometry produces reliable results, the data processing from gating to fingerprinting is prone to subjective bias. Here, we integrated autogating with Automated Machine Learning in flow cytometry to enhance the classification of bacter...
Escherichia coli Flow Cytometry Machine Learning Phenotype Bacteria
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Ensemble-learning approach improves fracture prediction using genomic and phenotypic data.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA Mar 7, 2025
UNLABELLED: This study presents an innovative ensemble machine learning model integrating genomic and clinical data to enhance the prediction of major osteoporotic fractures in older men. The Super Learner (SL) model achieved superior performance (AU...
Phenotype Bone Density Risk Factors Humans Machine Learning Algorithms Middle Aged Risk Assessment Genomics Osteoporotic Fractures Aged Aged, 80 and over Male
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Accurate phenotyping of luminal A breast cancer in magnetic resonance imaging: A new 3D CNN approach.

Computers in biology and medicine Mar 6, 2025
Breast cancer (BC) remains a predominant and deadly cancer in women worldwide. By 2040, projections indicate that more than 3 million new cases of breast cancer will emerge annually, culminating in more than 1 million deaths worldwide. Early detectio...
Imaging, Three-Dimensional Magnetic Resonance Imaging Neural Networks, Computer Phenotype Female Breast Neoplasms Middle Aged Deep Learning Humans
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Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Mar 6, 2025
OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using serum biomarkers can be determined solely from electronic health record (EHR) data using machine learn...
Machine Learning Phenotype Biomarkers Humans Male Infant Adolescent Child, Preschool Retrospective Studies Electronic Health Records Female Respiratory Distress Syndrome Child Intensive Care Units, Pediatric ROC Curve
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Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 6, 2025
Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framewo...
Genome-Wide Association Study Genomics Genotype Machine Learning Genome, Plant Zea mays Phenotype Gene-Environment Interaction Environment
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