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

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Multi-Neighborhood Search for Discrimination of Signal Peptides and Transmembrane Segmentsally be inserted in the membrane and which proteins would be secreted into the ER lumen when they cross the translocon channel. The aim of this work is to present an improvement of a previous method based on a local search approach. The proposed method relies on new in-depth biological observations

LEVER

Approximation of Graph Kernel Similarities for Chemical Graphs by Kernel Principal Component Analysire a graph transformation before the computation can be applied. Furthermore, the kernel calculation can have a polynomial complexity of degree three and higher. Therefore, they cannot be applied in large instance-based machine learning problems. By using kernel principal component analysis, we mapp

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Experimental Approach for Bacterial Strains Characterizationlt. In this work, we are particularly interested by the characterization of strains of phytopathogenic bacterias, which is an important issue in the study of plant diseases. We study and compare several methods computing the smallest possible characterizations. These experiments have allowed us to c

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Do Diseases Spreading on Bipartite Networks Have Some Evolutionary Advantage?t individuals of the two different families. This peculiar route is typical of diseases such as sexual transmitted diseases on heterosexual populations or vector-host diseases such as tick-borne encephalitis or Lyme borreliosis. In such epidemiological scenarios, the contact network is naturally rep

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Genetic Algorithm Optimization of Force Field Parameters: Application to a Coarse-Grained Model of R that is often performed manually. To improve this parametrization procedure we apply a continuous-space Genetic Algorithm (GA). GA is implemented to optimize parameters of a coarse-grained potential energy function of ribonucleic acid (RNA) molecules. The parameters obtained using GA are correctly

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An Automatic Identification and Resolution System for Protein-Related Abbreviations in Scientific Paic process implemented in our PRAISED framework. The identification of biological acronyms is carried out via an effective syntactical approach, by taking advantage of lexical clues and using mostly domain-independent metrics, resulting in considerably high levels of recall as well as extremely low

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Protein Complex Discovery from Protein Interaction Network with High False-Positive Rateotein complexes from protein-protein interaction(PPI) network originates from the fact that protein interactions suffer from high false positive rate. We propose a complex finding algorithm which is not strongly dependent on topological traits of the protein interaction network. Our method exploits

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