Background The paper reports extensive CFD work and analyses of an oscillatory baffled reactor (OBR) planned to be used for the production of polyaniline continuously. In the polyaniline process, viscosity changes during the course of the reaction. Two non‐Newtonian fluids were used to represent the stages of fluids during the reaction in a simulation, in addition to water as the reference fluid. Two quantitative measures derived from the CFD results are employed to evaluate OBR reactor performance: the axial dispersion coefficient and the ratio of axial and transverse velocities. Results The CFD data showed that the dispersion coefficient as a function of viscosity exhibits a maximum for given oscillation parameters. In the turbulent regime, the axial dispersion is often correlated with the oscillatory Reynolds number in OBR or equivalent Reynolds numbers in other reactor devices. In the high viscosity regime, such a general correlation is not valid for different operational parameters. The results of the CFD simulations in the moving baffle‐OBR indicate, for the first time, that the axial dispersion coefficients in the moving baffle arrangement is 10–17% higher than that in the moving fluid type, due to enhanced shear rate in the former device. This quantitative information is valuable for the design and smooth transition from batch to continuous reactors. Conclusion The established dependence of axial dispersion and the ratio of axial to transverse velocities on both viscosity and the operational parameters enhanced the understanding of mixing and dispersion characteristics of the OBR. The CFD analysis supplied the information needed to determine the design parameters for the reactor used in continuous production of polyaniline.© 2012 Society of Chemical Industry

Since the human genome was sequenced in draft, single nucleotide polymorphism (SNP) analysis has become one of the keynote fields of bioinformatics. We have developed an integrated database-tools system, rSNP_Guide (http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/), devoted to prediction of transcription factor (TF) binding sites, alterations of which could be associated with disease phenotype. By inputting data on alterations in DNA sequence and in DNA binding pattern of an unknown TF, rSNP_Guide searches for a known TF with alterations in the recognition score calculated on the basis of TF site's sequence and consistent with the input alterations in DNA binding to the unknown TF. Our system has been tested on many relationships between known TF sites and diseases, as well as on site-directed mutagenesis data. Experimental verification of rSNP_Guide system was made on functionally important SNPs in human TDO2and mouse K-ras genes. Additional examples of analysis are reported involving variants in the human gammaA-globin (HBG1), hsp70(HSPA1A), and Factor IX (F9) gene promoters.

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The analysis of gene regulatory networks has become one of the most challenging problems of the postgenomic era. Earlier we developed rSNP_Guide (http://util.bionet.nsc.ru/databases/rsnp.html), a computer system and database devoted to prediction of transcription factor (TF) binding sites (TF sites), which can be responsible for disease phenotypes. The prediction results were confirmed by 70 known relationships between TF sites and diseases, as well as by site-directed mutagenesis data. The rSNP_Guide is being investigated as a tool for TF site annotation. Previously analyzed and characterized cases of altered TF sites were used to annotate potential sites of the same type and at the same location in homologous genes. Based on 20 TF sites with known alterations in TF binding to DNA, we localized 245 potential TF sites in homologous genes. For these potential TF sites, rSNP_Guide estimates TF-DNA interaction according to three categories: 'present', 'weak', and 'absent'. The significance of each assignment is statistically measured.

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