AIMC Topic: Whole Genome Sequencing

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

American journal of human genetics Jan 14, 2022
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 ...
Genomic Structural Variation Genome, Human Exons Algorithms ROC Curve Genomics Whole Genome Sequencing Supervised Machine Learning Datasets as Topic Humans Software
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Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients.

Molecular psychiatry Jan 8, 2022
Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to ...
Humans Algorithms Deep Learning Minority Groups Whole Genome Sequencing Black or African American Ethnicity Attention Deficit Disorder with Hyperactivity
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Strengths and caveats of identifying resistance genes from whole genome sequencing data.

Expert review of anti-infective therapy Dec 16, 2021
INTRODUCTION: Antimicrobial resistance (AMR) continues to present major challenges to modern healthcare. Recent advances in whole-genome sequencing (WGS) have made the rapid molecular characterization of AMR a realistic possibility for diagnostic lab...
Humans Artificial Intelligence Anti-Bacterial Agents Whole Genome Sequencing Drug Resistance, Bacterial Microbial Sensitivity Tests
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Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma.

Acta neuropathologica communications Dec 4, 2021
Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigational study of diffuse gliomas in the modern era. While DNA sequencing is the gold standard for determining IDH mutational status, genome-wide methyla...
Biomarkers, Tumor Brain Neoplasms Glioma Humans Machine Learning DNA Copy Number Variations Whole Genome Sequencing Isocitrate Dehydrogenase
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Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

International journal of molecular sciences Dec 2, 2021
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...
Escherichia coli Mutation Whole Genome Sequencing Pseudomonas aeruginosa Genome, Bacterial Drug Resistance, Bacterial Anti-Infective Agents Genomics Machine Learning
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Personalized Cell Therapy for Patients with Peripheral Arterial Diseases in the Context of Genetic Alterations: Artificial Intelligence-Based Responder and Non-Responder Prediction.

Cells Nov 23, 2021
Stem/progenitor cell transplantation is a potential novel therapeutic strategy to induce angiogenesis in ischemic tissue, which can prevent major amputation in patients with advanced peripheral artery disease (PAD). Thus, clinicians can use cell ther...
Cell- and Tissue-Based Therapy Precision Medicine Risk Factors Transcriptome Genome-Wide Association Study Peripheral Arterial Disease Whole Genome Sequencing Humans Artificial Intelligence
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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 Oct 11, 2021
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...
Genome, Human Humans Genomic Structural Variation Deep Learning Models, Genetic Genomics Whole Genome Sequencing
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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...
Algorithms Africa Deep Learning Evolution, Molecular Bayes Theorem Whole Genome Sequencing Humans Fossils Genetic Variation Monte Carlo Method
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Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Experimental biology and medicine (Maywood, N.J.) Jul 7, 2021
Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogene...
Deep Learning Humans Genetic Predisposition to Disease Female Male Whole Genome Sequencing DNA Copy Number Variations Reproducibility of Results Case-Control Studies Black or African American Young Adult Attention Deficit Disorder with Hyperactivity
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HARVESTMAN: a framework for hierarchical feature learning and selection from whole genome sequencing data.

BMC bioinformatics Apr 1, 2021
BACKGROUND: Supervised learning from high-throughput sequencing data presents many challenges. For one, the curse of dimensionality often leads to overfitting as well as issues with scalability. This can bring about inaccurate models or those that re...
Genome Deep Learning Humans Genomics Breast Neoplasms Whole Genome Sequencing
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