Global quantitative biology can illuminate ontological connections between diseases

doi:10.1007/s40484-017-0104-7

Quant. Biol.

2017, Vol. 5

Issue (2) : 191-198 https://doi.org/10.1007/s40484-017-0104-7

PERSPECTIVE

Global quantitative biology can illuminate ontological connections between diseases

Guanyu Wang(

)

Department of Biology, Southern University of Science and Technology, Shenzhen 518055, China

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Abstract

Owing to its interdisciplinary nature, quantitative biology is playing ever-increasing roles in biological researches. To make quantitative biology even more powerful, it is important to develop a holistic perspective by integrating information from multiple biological levels and by considering related biocomplexity simultaneously. Using complex diseases as an example, I show in this paper how their ontological connections can be revealed by considering the diseases on a common ground. The obtained insights may be useful to the prediction and treatment of the diseases. Although the example involves only with cancer and diabetes, the approaches are applicable to the study of other diseases, or even to other biological problems.

Author Summary Deep connections may exist between seemingly disparate things. Using complex diseases as an example, the author shows that the connections between diseases can be revealed by using powerful approaches of mathematics and quantitative biology. The obtained insights may be useful to the prediction and treatment of the diseases. It is promising to apply the approaches to study other biological problems.

Keywords quantitative biology disease modeling systems biology nonlinear dynamics

Corresponding Author(s): Guanyu Wang

Online First Date: 24 April 2017 Issue Date: 07 June 2017

Cite this article:

Guanyu Wang. Global quantitative biology can illuminate ontological connections between diseases[J]. Quant. Biol., 2017, 5(2): 191-198.

URL:

https://academic.hep.com.cn/qb/EN/10.1007/s40484-017-0104-7
https://academic.hep.com.cn/qb/EN/Y2017/V5/I2/191

Fig.1 Evolution of diseases.

Fig.2 The four types of nonpersistent points (the middle column) and their perturbations (the left and right columns).

Fig.3 A phase diagram of physiologic and pathologic phenotypes arising from the PI3K/Akt/mTOR pathway.

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