AIMC Topic: INDEL Mutation

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INDELpred: Improving the prediction and interpretation of indel pathogenicity within the clinical genome.

HGG advances Jul 10, 2024
Small insertions and deletions (indels) are critical yet challenging genetic variations with significant clinical implications. However, the identification of pathogenic indels from neutral variants in clinical contexts remains an understudied proble...
Humans Computational Biology Genome, Human Gene Frequency INDEL Mutation Machine Learning Software Genomics
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Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods.

Forensic science international May 21, 2024
Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures an...
Humans Genetics, Population East Asian People DNA Fingerprinting Ethnicity Machine Learning Gene Frequency China Polymorphism, Genetic INDEL Mutation
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Streamline unsupervised machine learning to survey and graph indel-based haplotypes from pan-genomes.

Molecular plant May 18, 2023
Genome INDEL Mutation Algorithms Unsupervised Machine Learning Haplotypes
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MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning.

Genome medicine Oct 8, 2022
Multiple computational approaches have been developed to improve our understanding of genetic variants. However, their ability to identify rare pathogenic variants from rare benign ones is still lacking. Using context annotations and deep learning me...
Deep Learning Computational Biology Nucleotides INDEL Mutation
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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 ...
ROC Curve Polymorphism, Single Nucleotide Computational Biology Biomarkers, Tumor Neoplasms Deep Learning High-Throughput Nucleotide Sequencing INDEL Mutation Oncogenes Databases, Genetic Models, Statistical Genetic Variation Machine Learning Algorithms Humans Neural Networks, Computer
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NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks.

Genome biology Sep 6, 2021
Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep learning method NanoCaller, which detects SNPs usin...
Chromosome Mapping Major Histocompatibility Complex Nanopore Sequencing Base Sequence Genome, Human INDEL Mutation Alleles High-Throughput Nucleotide Sequencing Haplotypes Humans Nanoparticles Neural Networks, Computer Benchmarking Polymorphism, Single Nucleotide
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HELLO: improved neural network architectures and methodologies for small variant calling.

BMC bioinformatics Aug 14, 2021
BACKGROUND: Modern Next Generation- and Third Generation- Sequencing methods such as Illumina and PacBio Circular Consensus Sequencing platforms provide accurate sequencing data. Parallel developments in Deep Learning have enabled the application of ...
High-Throughput Nucleotide Sequencing INDEL Mutation Humans Neural Networks, Computer
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Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Nature communications Jun 10, 2021
Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the induction of new rearrangements is poorly established. Here, we analyze a global set of telomere-to-telomere...
Pedigree Meiosis Eukaryota Chromosomes Arabidopsis Genome INDEL Mutation Genetic Variation Polymorphism, Genetic Ascomycota Polymorphism, Single Nucleotide Computer Simulation Sequence Inversion Models, Genetic Phylogeny Evolution, Molecular Retroelements Genome-Wide Association Study Machine Learning Crossing Over, Genetic Genomics Genes, Duplicate
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Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Oncogene Jun 11, 2020
Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in cancer genomes occur due to internal and external mutagenesis forces. Decoding the mutational processes by examining their unique patterns has successfu...
Deep Learning DNA Genome, Human Humans Neoplasms INDEL Mutation Point Mutation
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Ranking of non-coding pathogenic variants and putative essential regions of the human genome.

Nature communications Nov 20, 2019
A gene is considered essential if loss of function results in loss of viability, fitness or in disease. This concept is well established for coding genes; however, non-coding regions are thought less likely to be determinants of critical functions. H...
Chromatin Gene Expression Genetic Variation Humans Genome, Human Mutation Enhancer Elements, Genetic Introns Computer Simulation Nucleic Acid Conformation Genes, Reporter INDEL Mutation Supervised Machine Learning DNA
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