AIMC Topic: High-Throughput Nucleotide Sequencing

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ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

Microbiome May 9, 2024
BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identific...
Anti-Bacterial Agents Drug Resistance, Bacterial Deep Learning Humans Neural Networks, Computer Drug Resistance, Microbial High-Throughput Nucleotide Sequencing Genes, Bacterial Bacteria Computational Biology
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Prediction and causal inference of hyperuricemia using gut microbiota.

Scientific reports Apr 30, 2024
Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as gout and renal urinary calculus. Prolonged HUA is often associated with hypertension, atherosclerosis, diabetes mellitus, and chronic kidney disease....
Male Middle Aged Feces Female Adult Hyperuricemia Uric Acid High-Throughput Nucleotide Sequencing Gastrointestinal Microbiome RNA, Ribosomal, 16S Humans Machine Learning
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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...
DNA Lipopolysaccharides High-Throughput Nucleotide Sequencing Robotics Workflow Whole Genome Sequencing Humans Gene Library Reproducibility of Results
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A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing.

Nature communications Feb 16, 2024
Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequenc...
Deep Learning Sequence Analysis, DNA Nanopores DNA Methylation Nanopore Sequencing High-Throughput Nucleotide Sequencing
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MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

BMC bioinformatics Feb 7, 2024
BACKGROUND: The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This i...
Artificial Intelligence Machine Learning Algorithms Escherichia coli Software Bayes Theorem High-Throughput Nucleotide Sequencing Arabidopsis Staphylococcus aureus Sequence Analysis, DNA
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Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.

Molecular biotechnology Feb 3, 2024
Synthetic antibodies (Abs) represent a category of engineered proteins meticulously crafted to replicate the functions of their natural counterparts. Such Abs are generated in vitro, enabling advanced molecular alterations associated with antigen rec...
Protein Engineering Humans Antibodies Big Data Artificial Intelligence High-Throughput Nucleotide Sequencing
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Advances in next-generation sequencing and emerging technologies for hematologic malignancies.

Haematologica Feb 1, 2024
Innovations in molecular diagnostics have often evolved through the study of hematologic malignancies. Examples include the pioneering characterization of the Philadelphia chromosome by cytogenetics in the 1970s, the implementation of polymerase chai...
Mutation High-Throughput Nucleotide Sequencing Polymerase Chain Reaction Artificial Intelligence Hematologic Neoplasms Humans
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Performance analysis of conventional and AI-based variant callers using short and long reads.

BMC bioinformatics Dec 14, 2023
BACKGROUND: The accurate detection of variants is essential for genomics-based studies. Currently, there are various tools designed to detect genomic variants, however, it has always been a challenge to decide which tool to use, especially when vario...
Artificial Intelligence Software High-Throughput Nucleotide Sequencing Genomics Sequence Analysis, DNA
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Generating bulk RNA-Seq gene expression data based on generative deep learning models and utilizing it for data augmentation.

Computers in biology and medicine Dec 7, 2023
Large-scale high-throughput transcriptome sequencing data holds significant value in biomedical research. However, practical challenges such as difficulty in sample acquisition often limit the availability of large sample sizes, leading to decreased ...
Transcriptome Reproducibility of Results Deep Learning RNA-Seq High-Throughput Nucleotide Sequencing
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Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision.

Science advances Nov 8, 2023
Owing to the nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, ar...
High-Throughput Nucleotide Sequencing Gene Expression Profiling Escherichia coli Escherichia coli Proteins Gene Expression Deep Learning
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