AIMC Topic: Whole Genome Sequencing

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An Explainable Deep Learning Classifier of Bovine Mastitis Based on Whole-Genome Sequence Data-Circumventing the p >> n Problem.

International journal of molecular sciences Apr 26, 2024
The serious drawback underlying the biological annotation of whole-genome sequence data is the p >> n problem, which means that the number of polymorphic variants (p) is much larger than the number of available phenotypic records (n). We propose a wa...
Whole Genome Sequencing Mastitis, Bovine Deep Learning Cattle Genetic Predisposition to Disease Polymorphism, Single Nucleotide Genotype Female Animals
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Automating the Illumina DNA library preparation kit for whole genome sequencing applications on the flowbot ONE liquid handler robot.

Scientific reports Apr 8, 2024
Whole-genome sequencing (WGS) is currently making its transition from research tool into routine (clinical) diagnostic practice. The workflow for WGS includes the highly labor-intensive library preparations (LP), one of the most critical steps in the...
Humans Reproducibility of Results Lipopolysaccharides Whole Genome Sequencing High-Throughput Nucleotide Sequencing Gene Library Robotics DNA Workflow
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Deciphering complex antibiotic resistance patterns in through whole genome sequencing and machine learning.

Frontiers in cellular and infection microbiology Jan 4, 2024
INTRODUCTION: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp us...
Whole Genome Sequencing Clarithromycin Helicobacter Infections Helicobacter pylori Amoxicillin Drug Resistance, Microbial Humans Anti-Bacterial Agents Machine Learning Drug Resistance, Bacterial Microbial Sensitivity Tests
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Improving variant calling using population data and deep learning.

BMC bioinformatics May 12, 2023
Large-scale population variant data is often used to filter and aid interpretation of variant calls in a single sample. These approaches do not incorporate population information directly into the process of variant calling, and are often limited to ...
Genome-Wide Association Study Polymorphism, Single Nucleotide Whole Genome Sequencing Humans Deep Learning Gene Frequency High-Throughput Nucleotide Sequencing Genome, Human
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Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning.

Genome medicine Mar 16, 2023
BACKGROUND: Rapidly and efficiently identifying critically ill infants for whole genome sequencing (WGS) is a costly and challenging task currently performed by scarce, highly trained experts and is a major bottleneck for application of WGS in the NI...
Infant, Newborn Natural Language Processing Whole Genome Sequencing Machine Learning Phenotype Intensive Care Units, Neonatal Humans
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Haplotype and population structure inference using neural networks in whole-genome sequencing data.

Genome research Aug 25, 2022
Accurate inference of population structure is important in many studies of population genetics. Here we present HaploNet, a method for performing dimensionality reduction and clustering of genetic data. The method is based on local clustering of phas...
Whole Genome Sequencing Haplotypes Genome, Human Genetics, Population Humans Neural Networks, Computer Principal Component Analysis
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Classification of non-coding variants with high pathogenic impact.

PLoS genetics Apr 29, 2022
Whole genome sequencing is increasingly used to diagnose medical conditions of genetic origin. While both coding and non-coding DNA variants contribute to a wide range of diseases, most patients who receive a WGS-based diagnosis today harbour a prote...
Humans Machine Learning Software Mutation Whole Genome Sequencing
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Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing.

Journal of translational medicine Apr 28, 2022
BACKGROUND: The circadian system is responsible for regulating various physiological activities and behaviors and has been gaining recognition. The circadian rhythm is adjusted in a 24-h cycle and has transcriptional-translational feedback loops. Whe...
Circadian Rhythm Humans Artificial Intelligence Neural Networks, Computer Metabolic Syndrome Whole Genome Sequencing
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Phenotype-Based Threat Assessment.

Proceedings of the National Academy of Sciences of the United States of America Apr 1, 2022
Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pa...
Virulence Genome, Bacterial Machine Learning Phenotype Bacteria Whole Genome Sequencing Virulence Factors
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Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Scientific reports Feb 14, 2022
Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic s...
Phenotype Mycobacterium tuberculosis Prognosis Tuberculosis, Multidrug-Resistant Phylogeny Data Accuracy Cohort Studies Humans Whole Genome Sequencing Genome, Bacterial Deep Learning Mutation Microbial Sensitivity Tests Antitubercular Agents Drug Resistance, Multiple, Bacterial
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