Abstract
Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides that are not translated into proteins. They have recently gained widespread attention due to the finding that tens of thousands of lncRNAs reside in the human genome, and due to an increasing number of lncRNAs that are found to be associated with disease. Some lncRNAs, including disease-associated ones, play different roles in regulating the cell cycle. Mathematical models of the cell cycle have been useful in better understanding this biological system, such as how it could be robust to some perturbations and how the cell cycle checkpoints could act as a switch. Here, we discuss mathematical modeling techniques for studying lncRNA regulation of the mammalian cell cycle. We present examples on how modeling via network analysis and differential equations can provide novel predictions toward understanding cell cycle regulation in response to perturbations such as DNA damage.
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Acknowledgments
This work is dedicated to the memory of Dr. Baltazar D. Aguda. JFR is supported by the PCARI-CHED IHITM 2017-018 project: Glycoproteomics of Filipino lung cancer cell lines for biomarker discovery and anti-cancer screening of natural products.
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Rabajante, J.F., del Rosario, R.C.H. (2019). Modeling Long ncRNA-Mediated Regulation in the Mammalian Cell Cycle. 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_17
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DOI: https://doi.org/10.1007/978-1-4939-8982-9_17
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