AIMC Topic: Genetic Variation

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Relating enhancer genetic variation across mammals to complex phenotypes using machine learning.

Science (New York, N.Y.) Apr 28, 2023
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challe...
Machine Learning Phenotype Animals Mammals Genetic Variation Enhancer Elements, Genetic
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Estimating resistance surfaces using gradient forest and allelic frequencies.

Molecular ecology resources Mar 10, 2023
Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity methods that use link-based methods traditionally rely on relating pairwise genetic distance between ...
Biodiversity Genetic Variation Gene Frequency Genetics, Population Computer Simulation
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Expectile Neural Networks for Genetic Data Analysis of Complex Diseases.

IEEE/ACM transactions on computational biology and bioinformatics Feb 6, 2023
The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identifie...
Linear Models Neural Networks, Computer Phenotype Genetic Variation
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Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning.

Microbiology spectrum Dec 13, 2022
The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge due to the genetic and antigenic variability of the causative virus (PRRSV). Predominantly, PRRSV management includes using vaccines and live virus in...
Machine Learning Animals Porcine Reproductive and Respiratory Syndrome Porcine respiratory and reproductive syndrome virus Swine Antigenic Variation Phylogeny Cross Protection Genetic Variation Cross Reactions
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A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization.

Scientific reports Feb 15, 2022
Genomic variant interpretation is a critical step of the diagnostic procedure, often supported by the application of tools that may predict the damaging impact of each variant or provide a guidelines-based classification. We propose the application o...
Humans Machine Learning Software Genomics Genetic Predisposition to Disease Logistic Models Bayes Theorem Research Design Computer Simulation Neoplasms Cohort Studies Practice Guidelines as Topic Genome, Human Genetic Testing Genetic Variation High-Throughput Nucleotide Sequencing
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Machine learning random forest for predicting oncosomatic variant NGS analysis.

Scientific reports Nov 8, 2021
Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but ...
Humans Neural Networks, Computer Machine Learning INDEL Mutation Algorithms Oncogenes Biomarkers, Tumor Databases, Genetic Neoplasms Models, Statistical Deep Learning ROC Curve Genetic Variation Polymorphism, Single Nucleotide High-Throughput Nucleotide Sequencing Computational Biology
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The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.

BMC cancer Nov 5, 2021
BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherap...
Oncogenic Viruses Tumor Virus Infections Kaplan-Meier Estimate Papillomaviridae DNA, Viral Epstein-Barr Virus Infections Herpesvirus 4, Human Mutation Leukocytes Genetic Variation High-Throughput Nucleotide Sequencing Genome, Viral Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Support Vector Machine Transcriptome Humans RNA-Seq Machine Learning Immunotherapy Stomach Neoplasms Tumor Microenvironment Biomarkers, Tumor Neoplasms
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Disease variant prediction with deep generative models of evolutionary data.

Nature Oct 27, 2021
Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences. In principle, computational...
Evolution, Molecular Selection, Genetic Humans Proteins Genetic Fitness Bayes Theorem Phenotype Unsupervised Machine Learning Genetic Predisposition to Disease Biological Assay Models, Molecular Genetic Variation Disease
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Revisiting the out of Africa event with a deep-learning approach.

American journal of human genetics Oct 8, 2021
Anatomically modern humans evolved around 300 thousand years ago in Africa. They started to appear in the fossil record outside of Africa as early as 100 thousand years ago, although other hominins existed throughout Eurasia much earlier. Recently, s...
Fossils Bayes Theorem Humans Whole Genome Sequencing Algorithms Africa Genetic Variation Deep Learning Monte Carlo Method Evolution, Molecular
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Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships.

Nature communications Sep 24, 2021
Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we add...
Zea mays Genomics Nitrogen Machine Learning Genotype Species Specificity Genetic Variation Phenotype Models, Genetic Genome, Plant Transcriptome Evolution, Molecular Gene Expression Regulation, Plant Arabidopsis
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