AIMC Topic: Genotype
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Sex identification in rainbow trout using genomic information and machine learning.
Genetics, selection, evolution : GSE
Dec 30, 2024
Sex identification in farmed fish is important for the management of fish stocks and breeding programs, but identification based on visual characteristics is typically difficult or impossible in juvenile or premature fish. The amount of genomic data ...
Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.
Aging cell
Dec 25, 2024
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...
Deep learning radiomics nomograms predict Isocitrate dehydrogenase (IDH) genotypes in brain glioma: A multicenter study.
Magnetic resonance imaging
Dec 19, 2024
PURPOSE: To explore the feasibility of Deep learning radiomics nomograms (DLRN) in predicting IDH genotype.
Cropformer: An interpretable deep learning framework for crop genomic prediction.
Plant communications
Dec 16, 2024
Machine learning and deep learning are extensively employed in genomic selection (GS) to expedite the identification of superior genotypes and accelerate breeding cycles. However, a significant challenge with current data-driven deep learning models ...
Genotype-negative multiple endocrine neoplasia type 1 with prolactinoma, hyperparathyroidism, and subclinical Cushing's syndrome accompanied by hyperglycemia: a case report.
Frontiers in endocrinology
Dec 12, 2024
BACKGROUND: Multiple endocrine neoplasia type 1 (MEN1) is a rare autosomal dominant disorder, accompanied by multiple endocrine neoplasms of the parathyroid, pancreas, pituitary, and other neoplasms in the adrenal glands. However, in some cases, pati...
Machine learning approaches and genetic determinants that influence the development of type 2 diabetes mellitus: a genetic association study in Brazilian patients.
Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
Dec 2, 2024
This genetic association study including 120 patients with type 2 diabetes mellitus (T2DM) and 166 non-diabetic individuals aimed to investigate the association of polymorphisms in the genes GSTM1 and GSTT1 (gene deletion), GSTP1 (rs1695), ACE (rs464...
Case-Control Studies
Diabetes Mellitus, Type 2
Genetic Predisposition to Disease
Polymorphism, Single Nucleotide
Adult
Humans
Male
Middle Aged
Brazil
Machine Learning
Female
Polymorphism, Genetic
Genotype
Risk Factors
Glutathione S-Transferase pi
Genetic Association Studies
Aged
Vascular Endothelial Growth Factor A
Glutathione Transferase
Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis.
The Plant journal : for cell and molecular biology
Nov 27, 2024
Cannabis sativa L., known for its medicinal and psychoactive properties, has recently experienced rapid market expansion but remains understudied in terms of its fundamental biology due to historical prohibitions. This pioneering study implements GS ...
Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant from whole genome sequencing and gene expression.
Antimicrobial agents and chemotherapy
Nov 14, 2024
Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susce...
Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning.
Journal of agricultural and food chemistry
Nov 13, 2024
Proteomics can be used to assess individual protein abundances, which could reflect genotypic and environmental effects and potentially predict grain/malt quality. In this study, 79 barley grain samples (genotype-location-year combinations) from Cali...
Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations.
European journal of medical research
Nov 10, 2024
BACKGROUND: Methylmalonic acidemia (MMA) is one of the most common hereditary organic acid metabolism disorders that endangers the lives and health of infants and children. Early detection and intervention before the appearance of a newborn's clinica...
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