Titlebook: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics; 10th European Confer Mario Giacobini,Leonardo Vanneschi,Willi

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Optimizing the Edge Weights in Optimal Assignment Methods for Virtual Screening with Particle Swarm nce. We compared the optimal assignment with optimized edge weights to the original version with equal weights on various benchmark data sets using sophisticated virtual screening performance metrics. The results show that the optimal assignment with optimized edge weights achieved a considerably be

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The Role of Mutations in Whole Genome Duplicationin a mixed population, ensuring the spreading novel phenotype. We conclude that both types of mutations play complementary roles in determining the successful propagation of organisms with duplicated genomes.

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Prediction of Mitochondrial Matrix Protein Structures Based on Feature Selection and Fragment Assemb which were used to predictions. We tested our proposal on 74 mitochondrial matrix proteins with a maximum sequence identity of 30% obtained from the Protein Data Bank. We achieved a recall of 0.80 and a precision of 0.79 with an 8-angstrom cut-off and a minimum sequence separation of 7 amino acids.

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Feature Selection for Lung Cancer Detection Using SVM Based Recursive Feature Elimination Methodd texture. We obtained an accuracy of 80% using the current feature set. In order to improve the accuracy of our method, we performed feature selection on these 79 features. We used Support Vector Machine (SVM) based Recursive feature Elimination (RFE) method in our experiments. We obtained an accur

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Measuring Gene Expression Noise in Early , Embryos: The Highly Dynamic Compartmentalized Micro-envirow that the ‘texture noise’, arising from the pre-cellular compartmentalization of the embryo surface, which is highly dynamic in time, is a major component of total biological noise, and can exceed gene transcription/translation noise.

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0302-9743 ce, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.978-3-642-29065-7978-3-642-29066-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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https://doi.org/10.1007/978-3-030-61537-6nce. We compared the optimal assignment with optimized edge weights to the original version with equal weights on various benchmark data sets using sophisticated virtual screening performance metrics. The results show that the optimal assignment with optimized edge weights achieved a considerably be