AIMC Topic: High-Throughput Nucleotide Sequencing

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An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives.

Computers in biology and medicine Mar 6, 2025
UNLABELLED: Infectious diseases, including tuberculosis (TB), HIV/AIDS, and emerging pathogens like COVID-19 pose severe global health challenges due to their rapid spread and significant morbidity and mortality rates. Next-generation sequencing (NGS...
Communicable Diseases SARS-CoV-2 High-Throughput Nucleotide Sequencing Humans Machine Learning COVID-19 Algorithms
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EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs.

International journal of biological macromolecules Mar 6, 2025
Long non-coding RNAs (lncRNAs) play key roles in numerous biological processes and are associated with various human diseases. High-throughput RNA sequencing (HTlncRNAs) has identified tens of thousands of lncRNAs across species, but only a small fra...
Humans Neural Networks, Computer Animals Deep Learning Mice Computational Biology Sequence Analysis, RNA RNA, Long Noncoding High-Throughput Nucleotide Sequencing
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Data stewardship and curation practices in AI-based genomics and automated microscopy image analysis for high-throughput screening studies: promoting robust and ethical AI applications.

Human genomics Feb 23, 2025
BACKGROUND: Researchers have increasingly adopted AI and next-generation sequencing (NGS), revolutionizing genomics and high-throughput screening (HTS), and transforming our understanding of cellular processes and disease mechanisms. However, these a...
Image Processing, Computer-Assisted Genomics Microscopy High-Throughput Nucleotide Sequencing High-Throughput Screening Assays Data Curation Humans Artificial Intelligence
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A Perspective on Artificial Intelligence for Molecular Pathologists.

The Journal of molecular diagnostics : JMD Feb 13, 2025
The widespread adoption of next-generation sequencing technology in molecular pathology has enabled us to interrogate the genome as never before. The huge quantities of data generated by sequencing, the enormous complexity of human and microbial gene...
High-Throughput Nucleotide Sequencing Pathology, Molecular Machine Learning Computational Biology Pathologists Humans Artificial Intelligence
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Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy.

Journal of cancer research and clinical oncology Feb 9, 2025
INTRODUCTION: For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplific...
Deep Learning Antineoplastic Combined Chemotherapy Protocols Neoadjuvant Therapy Breast Neoplasms Biomarkers, Tumor Middle Aged Mutation High-Throughput Nucleotide Sequencing Receptor, ErbB-2 Humans Prognosis Female Adult
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An Information Fusion System-Driven Deep Neural Networks With Application to Cancer Mortality Risk Estimate.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Next-generation sequencing (NGS) genomic data offer valuable high-throughput genomic information for computational applications in medicine. Using genomic data to identify disease-associated genes to estimate cancer mortality risk remains challenging...
Humans Neural Networks, Computer Risk Assessment Fuzzy Logic High-Throughput Nucleotide Sequencing Genomics Neoplasms Squamous Cell Carcinoma of Head and Neck Deep Learning Head and Neck Neoplasms
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Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics.

Nature cancer Jan 29, 2025
The diagnostic landscape of brain tumors integrates comprehensive molecular markers alongside traditional histopathological evaluation. DNA methylation and next-generation sequencing (NGS) have become a cornerstone in central nervous system (CNS) tum...
Gene Expression Profiling Biomarkers, Tumor Transcriptome Brain Neoplasms Deep Learning DNA Methylation Humans Male High-Throughput Nucleotide Sequencing Female Central Nervous System Neoplasms
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Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.

Genome research Jan 22, 2025
The discovery of circulating fetal and tumor cell-free DNA (cfDNA) molecules in plasma has opened up tremendous opportunities in noninvasive diagnostics such as the detection of fetal chromosomal aneuploidies and cancers and in posttransplantation mo...
Machine Learning Female Neoplasms Humans Cell-Free Nucleic Acids Artificial Intelligence High-Throughput Nucleotide Sequencing Liquid Biopsy
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A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing.

Nature communications Jan 2, 2025
Microsatellite instability (MSI) is a critical phenotype of cancer genomes and an FDA-recognized biomarker that can guide treatment with immune checkpoint inhibitors. Previous work has demonstrated that next-generation sequencing data can be used to ...
Microsatellite Instability High-Throughput Nucleotide Sequencing Biomarkers, Tumor Humans Neoplasms Neural Networks, Computer Deep Learning Algorithms Software Prospective Studies
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High-Risk Sequence Prediction Model in DNA Storage: The LQSF Method.

IEEE transactions on nanobioscience Jan 2, 2025
Traditional DNA storage technologies rely on passive filtering methods for error correction during synthesis and sequencing, which result in redundancy and inadequate error correction. Addressing this, the Low Quality Sequence Filter (LQSF) was intro...
Humans Neural Networks, Computer Algorithms Deep Learning Computational Biology High-Throughput Nucleotide Sequencing Sequence Analysis, DNA DNA
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