{"title":"DeepLCRmiRNA: A Hybrid Neural Network Approach for Identifying Lung Cancer-Associated miRNAs.","authors":"Nitao Cheng, Chen Chen, Junliang Liu, Xuanchun Wang, Ziqi Gao, Ming Mao, Jingyu Huang","doi":"10.2174/0115665232312364240902060458","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Lung cancer stands as one of the most prevalent malignant neoplasms, with microRNAs (miRNAs) playing a pivotal role in the modulation of gene expression, impacting cancer cell proliferation, invasion, metastasis, immune escape, and resistance to therapy.</p><p><strong>Method: </strong>The intricate role of miRNAs in lung cancer underscores their significance as biomarkers for early detection and as novel targets for therapeutic intervention. Traditional approaches for the identification of miRNAs related to lung cancer, however, are impeded by inefficiencies and complexities.</p><p><strong>Results: </strong>In response to these challenges, this study introduced an innovative deep-learning strategy designed for the efficient and precise identification of lung cancer-associated miRNAs. Through comprehensive benchmark tests, our method exhibited superior performance relative to existing technologies.</p><p><strong>Conclusion: </strong>Further case studies have also confirmed the ability of our model to identify lung cancer-associated miRNAs that have undergone biological validation.</p>","PeriodicalId":10798,"journal":{"name":"Current gene therapy","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current gene therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115665232312364240902060458","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Lung cancer stands as one of the most prevalent malignant neoplasms, with microRNAs (miRNAs) playing a pivotal role in the modulation of gene expression, impacting cancer cell proliferation, invasion, metastasis, immune escape, and resistance to therapy.
Method: The intricate role of miRNAs in lung cancer underscores their significance as biomarkers for early detection and as novel targets for therapeutic intervention. Traditional approaches for the identification of miRNAs related to lung cancer, however, are impeded by inefficiencies and complexities.
Results: In response to these challenges, this study introduced an innovative deep-learning strategy designed for the efficient and precise identification of lung cancer-associated miRNAs. Through comprehensive benchmark tests, our method exhibited superior performance relative to existing technologies.
Conclusion: Further case studies have also confirmed the ability of our model to identify lung cancer-associated miRNAs that have undergone biological validation.
期刊介绍:
Current Gene Therapy is a bi-monthly peer-reviewed journal aimed at academic and industrial scientists with an interest in major topics concerning basic research and clinical applications of gene and cell therapy of diseases. Cell therapy manuscripts can also include application in diseases when cells have been genetically modified. Current Gene Therapy publishes full-length/mini reviews and original research on the latest developments in gene transfer and gene expression analysis, vector development, cellular genetic engineering, animal models and human clinical applications of gene and cell therapy for the treatment of diseases.
Current Gene Therapy publishes reviews and original research containing experimental data on gene and cell therapy. The journal also includes manuscripts on technological advances, ethical and regulatory considerations of gene and cell therapy. Reviews should provide the reader with a comprehensive assessment of any area of experimental biology applied to molecular medicine that is not only of significance within a particular field of gene therapy and cell therapy but also of interest to investigators in other fields. Authors are encouraged to provide their own assessment and vision for future advances. Reviews are also welcome on late breaking discoveries on which substantial literature has not yet been amassed. Such reviews provide a forum for sharply focused topics of recent experimental investigations in gene therapy primarily to make these results accessible to both clinical and basic researchers. Manuscripts containing experimental data should be original data, not previously published.