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A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
Published on: August 21, 2019
Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data
Li Huang1,2, Li Zhang3, Xing Chen3,4
1Academy of Arts and Design, Tsinghua University, Beijing, 10084, China.
Abstract:
MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.
Insights
MicroRNAs (miRNAs) regulate genes and are key to understanding complex diseases like cancer. Accurate discovery of miRNA-disease associations (MDAs) is crucial for developing effective diagnostics and therapies.
Area of Science:
- Biochemistry and Molecular Biology
- Genetics and Genomics
- Computational Biology
Background:
- MicroRNAs (miRNAs) are critical gene regulators implicated in complex diseases, notably cancers.
- Accurate identification of miRNA-disease associations (MDAs) is essential for developing miRNA-based diagnostics and therapeutics.
- Over 55,000 PubMed entries highlight the extensive research in MDA prediction over the past 15 years.
Approach:
- This review revisits miRNA biogenesis, detection methods, and functions.
- It summarizes recent experimental findings on common miRNA-associated diseases.
- The study introduces updated miRNA databases and novel releases since 2017, alongside new and mainstream web servers.
Key Points:
- Focuses on advancements in computational models for predicting miRNA-disease associations (MDAs).
- Highlights the fusion of diverse data sources for enhanced MDA prediction accuracy.
- Discusses recent experimental findings and updates in miRNA-relevant databases and web servers.
Conclusions:
- Accurate MDA prediction is vital for advancing miRNA-based diagnostics and therapies.
- The integration of multiple data sources significantly improves the accuracy of predicting miRNA-disease associations.
- This review serves as a continuation, updating the field since the 2017 comprehensive review on MDA prediction.
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