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Quality improvement of rule-based gene group descriptions using information about GO terms importance occurring in premises of determined rules

Marek Sikora, Aleksandra Gruca (2010)

International Journal of Applied Mathematics and Computer Science

In this paper we present a method for evaluating the importance of GO terms which compose multi-attribute rules. The rules are generated for the purpose of biological interpretation of gene groups. Each multi-attribute rule is a combination of GO terms and, based on relationships among them, one can obtain a functional description of gene groups. We present a method which allows evaluating the influence of a given GO term on the quality of a rule and the quality of a whole set of rules. For each...

Quasi-Monte Carlo Methods for some Linear Algebra Problems. Convergence and Complexity

Karaivanova, Aneta (2010)

Serdica Journal of Computing

We present quasi-Monte Carlo analogs of Monte Carlo methods for some linear algebra problems: solving systems of linear equations, computing extreme eigenvalues, and matrix inversion. Reformulating the problems as solving integral equations with a special kernels and domains permits us to analyze the quasi-Monte Carlo methods with bounds from numerical integration. Standard Monte Carlo methods for integration provide a convergence rate of O(N^(−1/2)) using N samples. Quasi-Monte Carlo methods...

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