Titlebook: Computational Life Sciences; First International Michael R. Berthold,Robert C. Glen,Ingrid Fischer Conference proceedings 2005 Springer-Ve

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Ferritin

Recurrent Neuro-fuzzy Network Models for Reverse Engineering Gene Regulatory Interactionsteractions retrieved from a set of genes known to be highly regulated during the yeast cell-cycle are validated by biological studies, while our method surpasses previous computational techniques that attempted gene networks reconstruction, being able to retrieve significantly more biologically valid relationships among genes.

enmesh

Protein Annotation by Secondary Structure Based Alignments (PASSTA)uences as good as possible. Therefore, we use the Waterman-Eggert algorithm to compute pairwise alignments of SSE sequences with the query. In a graph-based approach, we then select those alignments that reproduce the query in an optimal way. We discuss two examples to illustrate the potential (and possible pitfalls) of the method.

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MAPPIS: Multiple 3D Alignment of Protein-Protein Interfaceso assume similarity of sequential patterns or backbone patterns. We show its application to several biological examples, such as alignment of interfaces of G proteins with their effectors and regulators, as well as previously created clusters of interfaces... The program and supplementary information, including colored figures, can be found at: .

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Proponent

Efficiency Considerations in Solving Smoluchowski Equations for Rough Potentials rate matrix which leads to a considerable speedup of the computation. This technique, in combination with HDA, is applied to study the rebinding of carbon monoxide (CO) to native myoglobin (Mb) and a mutated protein (L29F), a process of fundamental importance in biophysics.

堅毅

Das Fundamentaltheorem der Quantorenlogikpressed genes. To address this problem, we link gene expression data to protein interaction data. For the gene products of co-expressed genes, we identify structural domains by sequence alignment and threading. Next, we use the protein structure interaction PSIMAP to find structurally interacting do

GUILT

Unvollst?ndigkeit und Unentscheidbarkeite centre of attention over the last few years mostly in the form of algorithms, exploring cluster relationships and dynamic interactions between gene variables, and programs that try to display the multidimensional microarray data in appropriate formats so that they make biological sense. In this pa

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Protoplasmatologia‘ Cell Biology Monographsll functions is currently one of the central goals in computational molecular biology. We propose an approach for inferring the complex causal relationships among genes from microarray experimental data based on a recurrent neuro-fuzzy method. The method derives information on the gene interactions

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