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High-Throughput Nucleotide Sequencing

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The Role of ctDNA in the Management of Non-Small-Cell Lung Cancer in the AI and NGS Era.

International journal of molecular sciences 39769431
Liquid biopsy (LB) involves the analysis of circulating tumour-derived DNA (ctDNA), providing a minimally invasive method for gathering both quantitative and qualitative information. Genomic analysis of ctDNA through next-generation sequencing (NGS) ...
Artificial Intelligence Biomarkers, Tumor Carcinoma, Non-Small-Cell Lung Circulating Tumor DNA High-Throughput Nucleotide Sequencing Humans Liquid Biopsy Lung Neoplasms Prognosis
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Trans-m5C: A transformer-based model for predicting 5-methylcytosine (m5C) sites.

Methods (San Diego, Calif.) 39742984
5-Methylcytosine (m5C) plays a pivotal role in various RNA metabolic processes, including RNA localization, stability, and translation. Current high-throughput sequencing technologies for m5C site identification are resource-intensive in terms of cos...
5-Methylcytosine Animals Computational Biology Deep Learning High-Throughput Nucleotide Sequencing Humans Mice Neural Networks, Computer RNA
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Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions.

BMC bioinformatics 39719572
BACKGROUND: Accurate prediction of copy number variations (CNVs) from targeted capture next-generation sequencing (NGS) data relies on effective normalization of read coverage profiles. The normalization process is particularly challenging due to hid...
Algorithms Data Analysis DNA Copy Number Variations Exome Sequencing High-Throughput Nucleotide Sequencing Humans Neural Networks, Computer Sequence Analysis, DNA
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Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non-Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score.

JCO clinical cancer informatics 39661913
PURPOSE: Precision oncology in non-small cell lung cancer (NSCLC) relies on biomarker testing for clinical decision making. Despite its importance, challenges like the lack of genomic oncology training, nonstandardized biomarker reporting, and a rapi...
Artificial Intelligence Biomarkers, Tumor Carcinoma, Non-Small-Cell Lung High-Throughput Nucleotide Sequencing Humans Lung Neoplasms Oncogenes Precision Medicine
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Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics.

Nature cancer 39880907
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...
Biomarkers, Tumor Brain Neoplasms Central Nervous System Neoplasms Deep Learning DNA Methylation Female Gene Expression Profiling High-Throughput Nucleotide Sequencing Humans Male Transcriptome
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Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.

Genome research 39843210
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...
Artificial Intelligence Cell-Free Nucleic Acids Female High-Throughput Nucleotide Sequencing Humans Liquid Biopsy Machine Learning Neoplasms
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A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing.

Nature communications 39746944
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 ...
Algorithms Biomarkers, Tumor Deep Learning High-Throughput Nucleotide Sequencing Humans Microsatellite Instability Neoplasms Neural Networks, Computer Prospective Studies Software
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Machine learning-optimized targeted detection of alternative splicing.

Nucleic acids research 39727154
RNA sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases that hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that gr...
Algorithms Alternative Splicing High-Throughput Nucleotide Sequencing Humans Machine Learning RNA-Seq Sequence Analysis, RNA
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A Perspective on Artificial Intelligence for Molecular Pathologists.

The Journal of molecular diagnostics : JMD 39954999
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...
Artificial Intelligence Computational Biology High-Throughput Nucleotide Sequencing Humans Machine Learning Pathologists Pathology, Molecular
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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 39923208
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...
Adult Antineoplastic Combined Chemotherapy Protocols Biomarkers, Tumor Breast Neoplasms Deep Learning Female High-Throughput Nucleotide Sequencing Humans Middle Aged Mutation Neoadjuvant Therapy Prognosis Receptor, ErbB-2
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