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Web tools to perform long non-coding RNAs analysis in oncology research
Shixing Gu1, Guangjie Zhang1,2, Qin Si1
1College of Medical Technology, Chengdu University of Traditional Chinese Medicine, No.1166 Liutai Road, Chengdu, Sichuan 611137, China.
Summary
Long non-coding RNAs (lncRNAs) play roles in cell biology and cancer. This review categorizes bioinformatics web tools to help researchers efficiently select resources for lncRNA analysis in oncology.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- Long non-coding RNAs (lncRNAs) are widely expressed and implicated in cellular processes.
- Aberrant lncRNA expression is linked to pathological conditions, particularly cancer.
- lncRNAs influence tumorigenesis and cancer progression by modulating various molecular mechanisms and signaling pathways.
Purpose of the Study:
- To review and categorize existing bioinformatics web tools for lncRNA analysis.
- To aid researchers in selecting appropriate tools for studying lncRNA mechanisms and tissue-specific expression patterns.
- To facilitate the identification of lncRNAs as potential diagnostic/prognostic markers or therapeutic targets in oncology.
Main Methods:
- Systematic review of bioinformatics web tools for lncRNA analysis.
- Categorization of tools based on their functions, data sources, and analysis methodologies.
- Illustration of practical examples using specific lncRNAs and selected web tools.
Main Results:
- Identified and reviewed numerous in silico databases and integrative online platforms for lncRNA research.
- Clarified the data sources, analysis methods, and evidence basis for each reviewed tool.
- Provided practical use cases to demonstrate the utility of these bioinformatics tools in oncology studies.
Conclusions:
- Bioinformatics analysis is a crucial first step in understanding lncRNA functions and expression.
- The proliferation of web tools necessitates a structured review to prevent redundant efforts.
- This review offers a convenient guide for researchers to efficiently choose suitable bioinformatics web tools for lncRNA studies in cancer research.
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