Abstract
The recent explosion in the number and diversity of non-coding RNAs (ncRNAs) identified by the large-scale technologies brings new challenges to the biomedical researchers – What are all these non-coding RNAs, how did they work, and most importantly, what is the relationship between them and complex diseases? Although some ncRNAs have been clearly characterized as risk biomarkers through biological experiments, there are still a limit number of known disease associated ncRNAs. Thus, bioinformatics methods have been widely used to predict candidate ncRNAs and disease associations. In this chapter, we will discuss several bioinformatics methods which have been developed to predict novel non-coding biomarkers. With such methods and tools, the prioritization and identification of complex-implicated ncRNAs is becoming a reality.
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Wang, P., Li, X. (2018). Genomic-Scale Prioritization of Disease-Related Non-coding RNAs. In: Li, X., Xu, J., Xiao, Y., Ning, S., Zhang, Y. (eds) Non-coding RNAs in Complex Diseases. Advances in Experimental Medicine and Biology, vol 1094. Springer, Singapore. https://doi.org/10.1007/978-981-13-0719-5_4
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DOI: https://doi.org/10.1007/978-981-13-0719-5_4
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