Abstract
Human diseases are not only associated to mutations in protein-coding genes. Contrary to what was thought decades ago, the human genome is largely transcribed which generates a large amount of nonprotein-coding RNAs (ncRNAs). Interestingly, these ncRNAs are not only able to perform biological functions and interact with other molecules such as proteins, but also have been reported involved in human diseases. In this book chapter, we review the recent research done on controllability methods related to associations between ncRNAs and human diseases. First, we introduce the bipartite complex network resulting from the interactions of ncRNAs and proteins. We then explain the theoretical background of controllability algorithms and apply these methods to the problem of identifying ncRNAs with critical roles in network control. Then, by performing statistical analyses we can answer the question on whether the subset of critical control ncRNAs is also enriched by human diseases. In addition, we review three-layer network models for prediction of ncRNA-disease associations.
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Acknowledgments
J.C.N. was partially supported by JSPS KAKENHI Grant Number JP25330351, and T.A. was partially supported by JSPS KAKENHI Grant Number 26540125. This research was partially supported by the Collaborative Research Program of Institute for Chemical Research, Kyoto University.
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Nacher, J.C., Akutsu, T. (2019). Controllability Methods for Identifying Associations Between Critical Control ncRNAs and Human Diseases. In: Lai, X., Gupta, S., Vera, J. (eds) Computational Biology of Non-Coding RNA. Methods in Molecular Biology, vol 1912. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8982-9_11
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DOI: https://doi.org/10.1007/978-1-4939-8982-9_11
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