AIMC Topic: Polymorphism, Single Nucleotide

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Sub-sampling graph neural networks for genomic prediction of quantitative phenotypes.

G3 (Bethesda, Md.) Nov 6, 2024
In genomics, use of deep learning (DL) is rapidly growing and DL has successfully demonstrated its ability to uncover complex relationships in large biological and biomedical data sets. With the development of high-throughput sequencing techniques, g...
Neural Networks, Computer Algorithms Phenotype Polymorphism, Single Nucleotide Models, Genetic Triticum Quantitative Trait Loci Animals Genome-Wide Association Study Genomics
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Influence of vitamin D and calcium-sensing receptor gene variants on calcium metabolism in end-stage renal disease: insights from machine learning analysis.

European review for medical and pharmacological sciences Nov 1, 2024
OBJECTIVE: End-stage renal disease (ESRD) commonly manifests with disrupted calcium balance, leading to renal osteodystrophy. We posited that variations in the genetic makeup of vitamin D and calcium-sensing receptors, specifically single nucleotide ...
Adult Cross-Sectional Studies Male Machine Learning Female Aged Receptors, Calcitriol Kidney Failure, Chronic Calcium Receptors, Calcium-Sensing Middle Aged Polymorphism, Single Nucleotide Vitamin D Humans
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Predicting Pancreatic Cancer in New-Onset Diabetes Cohort Using a Novel Model With Integrated Clinical and Genetic Indicators: A Large-Scale Prospective Cohort Study.

Cancer medicine Nov 1, 2024
INTRODUCTION: Individuals who develop new-onset diabetes have been identified as a high-risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this spec...
Early Detection of Cancer Pancreatic Neoplasms United Kingdom Adult Male Middle Aged Risk Assessment Polymorphism, Single Nucleotide Diabetes Mellitus Female Risk Factors Aged Humans Machine Learning Prospective Studies
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Interpretation of SNP combination effects on schizophrenia etiology based on stepwise deep learning with multi-precision data.

Briefings in functional genomics Sep 27, 2024
Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is unclear how they affect schizophrenia susceptibility through interactions of multiple SNPs. We propose a stepwise deep learning technique with multi-...
Deep Learning Genome-Wide Association Study Genetic Predisposition to Disease Polymorphism, Single Nucleotide Schizophrenia Humans
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RiceSNP-BST: a deep learning framework for predicting biotic stress-associated SNPs in rice.

Briefings in bioinformatics Sep 23, 2024
Rice consistently faces significant threats from biotic stresses, such as fungi, bacteria, pests, and viruses. Consequently, accurately and rapidly identifying previously unknown single-nucleotide polymorphisms (SNPs) in the rice genome is a critical...
Genome, Plant Genome-Wide Association Study Polymorphism, Single Nucleotide Oryza Stress, Physiological Software Deep Learning
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Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction.

Briefings in bioinformatics Sep 23, 2024
Predicting molecular processes using deep learning is a promising approach to provide biological insights for non-coding single nucleotide polymorphisms identified in genome-wide association studies. However, most deep learning methods rely on superv...
Computational Biology Supervised Machine Learning Genome, Human Regulatory Sequences, Nucleic Acid Deep Learning Genome-Wide Association Study Polymorphism, Single Nucleotide Humans Algorithms
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Predicting functional outcome in ischemic stroke patients using genetic, environmental, and clinical factors: a machine learning analysis of population-based prospective cohort study.

Briefings in bioinformatics Sep 23, 2024
Ischemic stroke (IS) is a leading cause of adult disability that can severely compromise the quality of life for patients. Accurately predicting the IS functional outcome is crucial for precise risk stratification and effective therapeutic interventi...
Humans Machine Learning China Genome-Wide Association Study ROC Curve Polymorphism, Single Nucleotide Ischemic Stroke Aged Male Middle Aged Prospective Studies Prognosis Female
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Scalable CNN-based classification of selective sweeps using derived allele frequencies.

Bioinformatics (Oxford, England) Sep 1, 2024
MOTIVATION: Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding fa...
Gene Frequency Selection, Genetic Machine Learning Algorithms Polymorphism, Single Nucleotide Humans Neural Networks, Computer
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Detection of pre-mRNA involved in abnormal splicing using Graph Neural Network and Nearest Correlation Method.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
BACKGROUND: DNA is the building block of genetic information, and is composed of alternating sequences of exons with genetic information and introns without no genetic information. DNA is damaged by normal metabolic activities and environmental facto...
RNA Splicing Graph Neural Networks ROC Curve Polymorphism, Single Nucleotide RNA Precursors Humans Neural Networks, Computer Algorithms
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Classification accuracy of machine learning algorithms for Chinese local cattle breeds using genomic markers.

Yi chuan = Hereditas Jul 1, 2024
Accurate breed classification is required for the conservation and utilization of farm animal genetic resources. Traditional classification methods mainly rely on phenotypic characterization. However, it is difficult to distinguish between the highly...
Support Vector Machine Genetic Markers Breeding Cattle Genomics Polymorphism, Single Nucleotide Genome Machine Learning Algorithms Animals China
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