AIMC Topic: High-Throughput Nucleotide Sequencing

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Improving viral annotation with artificial intelligence.

mBio Sep 4, 2024
Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environme...
Humans Genome, Viral Molecular Sequence Annotation Bacteriophages Metagenome Artificial Intelligence High-Throughput Nucleotide Sequencing Metagenomics
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A review on advancements in feature selection and feature extraction for high-dimensional NGS data analysis.

Functional & integrative genomics Aug 19, 2024
Recent advancements in biomedical technologies and the proliferation of high-dimensional Next Generation Sequencing (NGS) datasets have led to significant growth in the bulk and density of data. The NGS high-dimensional data, characterized by a large...
Humans Machine Learning Deep Learning High-Throughput Nucleotide Sequencing
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Holistic understanding of trimethoprim resistance in using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning.

mBio Aug 9, 2024
UNLABELLED: Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to...
Genome, Bacterial Trimethoprim Resistance Machine Learning Pneumococcal Infections Anti-Bacterial Agents Genome-Wide Association Study Humans Streptococcus pneumoniae Microbial Sensitivity Tests Mutation Trimethoprim High-Throughput Nucleotide Sequencing
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Utilizing Deep Neural Networks to Fill Gaps in Small Genomes.

International journal of molecular sciences Aug 4, 2024
With the widespread adoption of next-generation sequencing technologies, the speed and convenience of genome sequencing have significantly improved, and many biological genomes have been sequenced. However, during the assembly of small genomes, we st...
Algorithms Deep Learning Genomics Sequence Analysis, DNA Neural Networks, Computer Software Genome, Fungal Neurospora crassa High-Throughput Nucleotide Sequencing Saccharomyces cerevisiae Schizosaccharomyces
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Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning.

PLoS computational biology Jul 2, 2024
The classification of B cell lymphomas-mainly based on light microscopy evaluation by a pathologist-requires many years of training. Since the B cell receptor (BCR) of the lymphoma clonotype and the microenvironmental immune architecture are importan...
High-Throughput Nucleotide Sequencing Lymphoma, B-Cell Receptors, Antigen, B-Cell Machine Learning Algorithms Leukemia, Lymphocytic, Chronic, B-Cell Lymphoma, Large B-Cell, Diffuse Computational Biology B-Lymphocytes Humans
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Machine Learning-Based Etiologic Subtyping of Ischemic Stroke Using Circulating Exosomal microRNAs.

International journal of molecular sciences Jun 20, 2024
Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (E...
Female Aged Male Middle Aged Gene Expression Profiling Extracellular Vesicles Humans Exosomes Machine Learning Computational Biology High-Throughput Nucleotide Sequencing Biomarkers MicroRNAs Circulating MicroRNA Ischemic Stroke
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Machine Learning-Assisted Direct RNA Sequencing with Epigenetic RNA Modification Detection via Quantum Tunneling.

Analytical chemistry Jun 14, 2024
RNA sequence information holds immense potential as a drug target for diagnosing various RNA-mediated diseases and viral/bacterial infections. Massively parallel complementary DNA (c-DNA) sequencing helps but results in a loss of valuable information...
Humans Machine Learning RNA Epigenesis, Genetic Sequence Analysis, RNA High-Throughput Nucleotide Sequencing Quantum Theory
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NmTHC: a hybrid error correction method based on a generative neural machine translation model with transfer learning.

BMC genomics Jun 7, 2024
BACKGROUNDS: The single-pass long reads generated by third-generation sequencing technology exhibit a higher error rate. However, the circular consensus sequencing (CCS) produces shorter reads. Thus, it is effective to manage the error rate of long r...
Algorithms High-Throughput Nucleotide Sequencing Humans Neural Networks, Computer Machine Learning
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Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning.

Frontiers in cellular and infection microbiology May 23, 2024
BACKGROUND: Lower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Lever...
Metagenomics Respiratory Tract Infections Bronchoalveolar Lavage Fluid Bacteria Microbiota Young Adult Adult High-Throughput Nucleotide Sequencing Male Middle Aged Bronchiectasis Hospitalization Lung Metagenome Aged Adolescent Aged, 80 and over Humans Machine Learning Female
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WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

PloS one May 17, 2024
BACKGROUND: Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Asso...
High-Throughput Nucleotide Sequencing Copper-Transporting ATPases Hepatolenticular Degeneration Algorithms Deep Learning Humans Genetic Variation
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