AIMC Topic: Phenotype

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Genome-enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.

Animal genetics
This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregna...

Image-based phenotyping of disaggregated cells using deep learning.

Communications biology
The ability to phenotype cells is fundamentally important in biological research and medicine. Current methods rely primarily on fluorescence labeling of specific markers. However, there are many situations where this approach is unavailable or undes...

Interpretation of cluster structures in pain-related phenotype data using explainable artificial intelligence (XAI).

European journal of pain (London, England)
BACKGROUND: In pain research and clinics, it is common practice to subgroup subjects according to shared pain characteristics. This is often achieved by computer-aided clustering. In response to a recent EU recommendation that computer-aided decision...

Transfer learning enables prediction of CYP2D6 haplotype function.

PLoS computational biology
Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene whose protein product metabolizes more than 20% of clinically used drugs. Genetic variations in CYP2D6 are responsible for interindividual heterogeneity in drug response that can lead to drug ...

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

Interdisciplinary sciences, computational life sciences
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...

Application of ensemble learning to genomic selection in chinese simmental beef cattle.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
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 ...

Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning.

Scientific reports
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...

Predicting antimicrobial resistance using conserved genes.

PLoS computational biology
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...

Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
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...