Biotechnology and Genetic Engineering Reviews, Vol. 25 by Stephen E. Harding

By Stephen E. Harding

Containing more than a dozen original, significant evaluation articles from authors released in top journals and covering very important advancements in business, agricultural, and scientific functions of biotechnology, this most recent version from the well-established hardcover assessment sequence focuses totally on the genetic manipulation of organisms. masking concerns starting from gene expression and genetic rules to plant bioreactors and enzymatic processing, this reference will profit scholars within the fields of biochemistry, genetics, molecular biology, and pharmaceutical sciences.

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Shiraishi, F. A. (1992b). The tricarboxylic acid cycle in Dictyostelium discoideum. II. Evaluation of model consistency and robustness. J Biol Chem. 267: 38 R. Alves et al. 22919-22925. Shiraishi, F. A. (1992c). The tricarboxylic acid cycle in Dictyostelium discoideum. IV. Resolution of discrepancies between alternative methods of analysis. J Biol Chem. 267: 22934-22943. C. J. (2007). Mathematical modeling as a tool for investigating cell cycle control networks. Methods. 41: 238-247. O. M. (2004).

A. (1989b). A comparison of variant theories of intact biochemical systems. II. Flux-oriented and metabolic control theories. Math Biosci. 94: 195-238. Sorribas, A. A. (1989c). Strategies for representing metabolic pathways within biochemical systems theory: reversible pathways. Math Biosci. 94: 239-269. Sprinzak, D. B. (2005). Reconstruction of genetic circuits. Nature. 438: 443-448. , Palenik, B. and Xu, Y. (2006). Computational inference and experimental validation of the nitrogen assimilation regulatory network in cyanobacterium Synechococcus sp WH 8102.

40 A) Mathematical formalisms based on approximated kinetic representations 21 22 R. Alves et al. Figure 3. Predictions of the new steady-state concentrations as we change the independent variable X5 while keeping the operating point of the approximations constant. The cross between the two lines in each plot indicates the operating point of the approximation. Abbreviations: Log(Xi)=Yi; SC for Saturable and Cooperative; PL for Power-law; GMA for Generalized Mass Action; SS for S-System; and LL for Lin-log and (log)linear formalisms.

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