By Matthias Dehmer, Frank Emmert-Streib
"Many difficulties from the existence sciences could be forged right into a mathematical framework that's in keeping with a graph theoretic description. consequently a radical figuring out of such equipment is more and more vital for the information research and modeling of biochemical, organic and biomedical problems." "This ebook follows a brand new technique together with graph idea from a mathematical standpoint via learning functions of community established equipment in a context-specific demeanour. The e-book is written through popular specialists within the box and provides useful historical past info for a large viewers starting from, e.g., discrete arithmetic, utilized records, biostatistics, computational biology, desktop technology, desktop studying or platforms biology."--Jacket. Read more...
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Additional info for Analysis of complex networks : from biology to linguistics
1999) From molecular to modular cell biology. Nature, 420, C47–C52. G. (2007) Human ribosomal protein s13 regulates expression of its own gene at the splicing step by a feedback mechanism. , 35 (19), 6414–6423. Vicsek, T. (2002) Complexity: the bigger picture. Nature, 418, 131. , Doyle, J. (2002) Complexity and robustness. Proc. Natl Acad. Sci. USA, 99 (Suppl. 1), 2538–2545. Grassberger, P. (1986) Toward a quantitative theory of self-generated complexity. Int. J. Theor. , 25, 907–928. 25 26 Systems Biology 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 Adami, C.
Hence, the question of gaining new biological knowledge on individual genes or proteins from this approach often remains open. Although knowledge-based bottom-up approaches of modeling possess a certain appeal to biologists, successful modeling needs to overcome the gaps in understanding. Most protein–protein interactions remain unknown, and the underlying physics of interacting molecules require better attention. Until now, the inﬂuence of high molecule concentrations in the subcompartments of a cell environment on reaction rates is largely unknown, but the spatial distribution of reactants and their molecular crowding may well affect the reactions and their rates [76, 77]; an example of this is when explaining the symmetry breaking process of mitosis .
This formal framework on the orchestrated role of cellular gene network dynamics could serve as a potential explanation for stem cell differentiation and the reprogramming of differentiated back into pluripotent stem cells , or even cancer progression. The accumulation of genetic mutations over time would distort the attractor landscape such that it would eventually lead to an altered cellular response within the same cellular context . While the above suggestions are intuitive and appealing, their value must still be proven with respect to knowledge gain on the level of individual genes and proteins as potential targets for cell control and intervention.
Analysis of complex networks : from biology to linguistics by Matthias Dehmer, Frank Emmert-Streib