Structural analysis, biological networks

Koehler J, Rawlings C, Verrier P (2005). Linking experimental results, biological networks and sequence analysis methods using Ontologies and Generalised Data Structures. In Silica Biol. 5 33-44. 

Nakasako, M. (1999) Large-scale networks of hydration water molecules around bovine beta-trypsin revealed by cryogenic X-ray crystal structure analysis. Journal ofMolecular Biology, 289,547—564. 

Particularly in the preceding Chapter 6 we have seen the significance of sf ability properties for biological network models. This experience leads us to devote the present chapter to a development of quite general techniques for a stability analysis of networks. Such an analysis can be performed under two different aspects a thermodynamic aspect, which relates stability to thermodynamic properties of the network like entropy production and the second lawi and a nonthermodynamic aspect, which derives the stability properties from the mathematical structure of the differential equations represented by the network on the basis of a topological analysis. Sections 7.1 to 7.4 of this chapter will be devoted to the thermodynamic aspect and in Sections 7.5 to 7.7 we briefly describe a few simple techniques to obtain information on stability from a topological analysis. 

Urade, Y., el al. (2006b). Biochemical and structural characteristics of hematopoietic prostaglandin D synthase from evolutionary analysis to drug designing. Functional and Structural Biology on the Lipo-network, 2006, Transworld Research Network, Kerala, India, pp. 135-64. 

Nonetheless, the topological and stoichiometric analysis of metabolic networks is probably the most powerful computational approach to large-scale metabolic networks that is currently available. Stoichiometric analysis draws upon extensive work on the structure of complex reaction systems in physical chemistry in the 1970s and 1980s [59], and can be considered as one of the few theoretically mature areas of Systems Biology. While the variety and amount of applications of stoichiometric analysis prohibit any comprehensive summary, we briefly address some essential aspects in the following. 

In recent years the rapid development of high-sensitivity analytical techniques such as mass spectrometry (MS) and liquid chromatography (LC) supported the investigation of the endocannabinoids as part of a complex lipid network. The identification of lipid components of the endocannabinoid system can be achieved in a single analytical step by state-of-the-art platforms such as tandem mass spectrometry (MS/MS), which provides the detailed structural information necessary for characterization of lipids and increases specificity in complex biological matrices. Furthermore, the implementation of ionization techniques such as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) allow the coupling of LC to MS, and permits the separation and analysis of endocannabinoids with greater speed and accuracy. 

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