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Titlebook: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics; 9th European Confere Clara Pizzuti,Marylyn D. Ritchie,Mario G

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https://doi.org/10.1057/9781137315113terized by these four properties. We also include a statistical study for the propensities of contacts between each pair of amino acids, according to their types, hydrophobicity and polarity. Different experiments were also performed to determine the best selection of properties for the structure prediction among the cited properties.
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https://doi.org/10.1007/978-3-030-41540-2ith an average accuracy of 0.34, superior to the 0.25 obtained by the FNETCSS method. This shows that our algorithm improves the accuracy with respect to the methods compared, especially with the increase of protein length.
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Paris A. Tsartas,Dimitrios G. Lagosa new measure, GECSS(Gene Expression Condition Set Similarity) which considers mRNA expression data for a set of PPI. The complexes we found exhibit a higher match with reference complexes than the existing methods. Also we found several novel protein complexes, which are significantly enriched on Gene Ontology database.
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Applying Linear Models to Learn Regulation Programs in a Transcription Regulatory Module Networkquently, the process of learning the regulation program for the module becomes one of identifying transcription factors that are also differentially expressed in this contrast. The effectiveness of our algorithm is demonstrated by the experiments in a yeast benchmark dataset.
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An Evolutionary Approach for Protein Contact Map Predictionterized by these four properties. We also include a statistical study for the propensities of contacts between each pair of amino acids, according to their types, hydrophobicity and polarity. Different experiments were also performed to determine the best selection of properties for the structure prediction among the cited properties.
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Do Diseases Spreading on Bipartite Networks Have Some Evolutionary Advantage?resented by a bipartite graphs. In this article we determine that a pathogen agent spreading on a bipartite network can have some evolutionary benefits with respect to diffusing on standard unipartite networks.
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Genetic Algorithm Optimization of Force Field Parameters: Application to a Coarse-Grained Model of Rreproducing the dynamical behavior of an RNA helix and other RNA tertiary motifs. Therefore, GA can be a useful tool for force field parametrization of the effective potentials in coarse-grained molecular models.
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