AIMC Topic: Genetic Variation

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MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning.

International journal of molecular sciences Apr 19, 2021
BACKGROUND: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell...
Neural Networks, Computer Deep Learning Genetic Variation Exons Humans
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Refinement of the clinical variant interpretation framework by statistical evidence and machine learning.

Med (New York, N.Y.) Mar 11, 2021
BACKGROUND: Although the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation are used widely in clinical genetics, there is room for improvement of these knowledge-bas...
Amino Acids Humans Genetic Testing Machine Learning United States Genetic Variation
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Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning.

Nature communications Mar 8, 2021
Elucidating functionality in non-coding regions is a key challenge in human genomics. It has been shown that intolerance to variation of coding and proximal non-coding sequence is a strong predictor of human disease relevance. Here, we integrate into...
Deep Learning Genomics Sequence Analysis, DNA Whole Genome Sequencing Humans Genetic Variation Genome, Human DNA, Intergenic
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CADD-Splice-improving genome-wide variant effect prediction using deep learning-derived splice scores.

Genome medicine Feb 22, 2021
BACKGROUND: Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond...
RNA Splicing Exons Humans Genome-Wide Association Study Deep Learning Genetic Variation Base Sequence Introns
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Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.

Frontiers in immunology Feb 18, 2021
Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, div...
HIV Infections Proteome CD8-Positive T-Lymphocytes HLA Antigens Machine Learning Epitopes, T-Lymphocyte Peptides Viral Proteins Antigens, Viral HIV Genetic Variation Host-Pathogen Interactions Genome, Viral Humans
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Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

Trends in microbiology Jan 14, 2021
The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. This wealth of information has revealed an unanticipated degree of strain-to-strain genetic diversity w...
Machine Learning Phylogeny Genome, Bacterial Bacteria Genome-Wide Association Study Virulence Factors Genomics Virulence Genotype Genetic Variation
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A Revised Model of Anatomically Modern Human Expansions Out of Africa through a Machine Learning Approximate Bayesian Computation Approach.

Genes Dec 16, 2020
There is a wide consensus in considering Africa as the birthplace of anatomically modern humans (AMH), but the dispersal pattern and the main routes followed by our ancestors to colonize the world are still matters of debate. It is still an open ques...
Asia Biological Evolution History, Ancient Human Migration Hominidae Neanderthals Bayes Theorem Genetic Variation Genome, Human Racial Groups Africa Models, Theoretical Europe Humans Machine Learning Computer Simulation Animals
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DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Computational and mathematical methods in medicine Sep 1, 2020
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method fo...
Cost-Benefit Analysis Neural Networks, Computer Computational Biology Humans Genome, Human Software Whole Genome Sequencing Cloud Computing Deep Learning Genetic Variation High-Throughput Nucleotide Sequencing
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A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

Genes Aug 12, 2020
DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylate...
Humans Algorithms Biomarkers, Tumor Neoplasms DNA Methylation Genetic Variation Linear Models Gene Ontology Computational Biology Gene Expression Profiling Deep Learning Epigenesis, Genetic ROC Curve Gene Expression Regulation, Neoplastic Databases, Genetic
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Cross-species regulatory sequence activity prediction.

PLoS computational biology Jul 20, 2020
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...
Humans Neural Networks, Computer Genomics Genome, Human Machine Learning Algorithms Mutation Species Specificity Computational Biology Software Animals Hepatocytes Quantitative Trait Loci Databases, Genetic Epigenomics Mice Genetic Variation Sequence Analysis, DNA Models, Genetic Gene Expression Regulation Models, Statistical
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