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Genome, Human

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Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers.

PLoS computational biology
Read-depths (RDs) are frequently used in identifying structural variants (SVs) from sequencing data. For existing RD-based SV callers, it is difficult for them to determine breakpoints in single-nucleotide resolution due to the noisiness of RD data a...

Predicting environmentally responsive transgenerational differential DNA methylated regions (epimutations) in the genome using a hybrid deep-machine learning approach.

BMC bioinformatics
BACKGROUND: Deep learning is an active bioinformatics artificial intelligence field that is useful in solving many biological problems, including predicting altered epigenetics such as DNA methylation regions. Deep learning (DL) can learn an informat...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Scientific reports
Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and microsatellite instability (MSI) / mismatch repair deficient (dMMR) tumors have been reported to be high...

Decoding the effects of synonymous variants.

Nucleic acids research
Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs su...

Genetic data sharing and artificial intelligence in the era of personalized medicine based on a cross-sectional analysis of the Saudi human genome program.

Scientific reports
The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial i...

StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants.

American journal of human genetics
Whole-genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole-genome sequencing. Structural variants (SVs; genomic variants larger than 50 base ...

A Method for Localizing Non-Reference Sequences to the Human Genome.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
As the last decade of human genomics research begins to bear the fruit of advancements in precision medicine, it is important to ensure that genomics' improvements in human health are distributed globally and equitably. An important step to ensuring ...

The reactome pathway knowledgebase 2022.

Nucleic acids research
The Reactome Knowledgebase (https://reactome.org), an Elixir core resource, provides manually curated molecular details across a broad range of physiological and pathological biological processes in humans, including both hereditary and acquired dise...

A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization.

Scientific reports
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...

A deep learning framework for characterization of genotype data.

G3 (Bethesda, Md.)
Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for v...