Advances in Bioinformatics and Computational Biology: by Joao Carlos Setubal, Sergio Verjovski-Almeida PDF

By Joao Carlos Setubal, Sergio Verjovski-Almeida

ISBN-10: 3540280081

ISBN-13: 9783540280088

This booklet constitutes the refereed court cases of the Brazilian Symposium on Bioinformatics, BSB 2005, held in Sao Leopoldo, Brazil in July 2005.

The 15 revised complete papers and 10 revised prolonged abstracts awarded including three invited papers have been rigorously reviewed and chosen from fifty five submissions. The papers handle a large variety of present issues in computational biology and bioinformatics.

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Read or Download Advances in Bioinformatics and Computational Biology: Brazilian Symposium on Bioinformatics, BSB 2005, Sao Leopoldo, Brazil, July 27-29, 2005, Proceedings PDF

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Additional resources for Advances in Bioinformatics and Computational Biology: Brazilian Symposium on Bioinformatics, BSB 2005, Sao Leopoldo, Brazil, July 27-29, 2005, Proceedings

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Using this criterion, the MST will group in each level of the hierarchy subsets of one or more classes that are similar to each other according to their centroid. 2. Inverse of centroid distance: in this case, the weight of an arc (i, j) is given by 1/dE (µi , µj ), where dE is the Euclidean distance. The MST will group subsets of classes that are more distant according to their centroid. 3. Balanced subsets: inspired by ideas presented in [23], this criterion acts by grouping classes that have similar data distribution.

If after this transformation, any of the rows of the K matrix still has the same sign, then the flux vector is thermodynamically unfeasible, and we detect the presence of a cycle. By satisfying this condition we can eliminate the non-linear constraint in equation (5), transforming the non-linear problem into a linear one. The no-cycle feasibility condition is equivalent to solving the FBA problem with constraints (4) and (5). To satisfy equation (4), for a single row of the K matrix corresponding to a single cycle, at least one of the ∆µi should differ in sign from the other components in the ∆µ vector, which, when combined with equation (5), prevents the formation of thermodynamically unfeasible loops in the network.

For a given system of reactions in steady state, mass balance of the reactions restricts the space of possible fluxes or rates to the null space of the stoichiometric matrix [13]. This constraint is used in flux balance analysis (FBA). Formulating the problem in terms of fluxes we do not need detailed knowledge of the kinetic parameters inside the cell. In the absence of detailed knowledge about the kinetic parameters and enzyme concentrations, the FBA assumes that the metabolic flux vector in a biological network optimizes the production of growth or biomass, subject to the mass balance constraint.

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Advances in Bioinformatics and Computational Biology: Brazilian Symposium on Bioinformatics, BSB 2005, Sao Leopoldo, Brazil, July 27-29, 2005, Proceedings by Joao Carlos Setubal, Sergio Verjovski-Almeida

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