Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics [electronic resource] : 10th European Conference, EvoBIO 2012, Mlaga, Spain, April 11-13, 2012. Proceedings / edited by Mario Giacobini, Leonardo Vanneschi, William S. Bush.
Tipo de material:
TextoSeries Lecture Notes in Computer Science, 7246Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012Descripción: XIII, 255p. 76 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642290664Trabajos contenidos: SpringerLink (Online service)Tema(s): Computer science | Data structures (Computer science) | Computer software | Database management | Artificial intelligence | Bioinformatics | Computer Science | Computational Biology/Bioinformatics | Algorithm Analysis and Problem Complexity | Database Management | Artificial Intelligence (incl. Robotics) | Computation by Abstract Devices | Data StructuresFormatos físicos adicionales: Sin títuloClasificación CDD: 570.285 Clasificación LoC:QH324.2-324.25Recursos en línea: de clik aquí para ver el libro electrónico Springer eBooksResumen: This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, held in Mlaga, Spain, in April 2012 co-located with the Evo* 2012 events. The 15 revised full papers presented together with 8 poster papers were carefully reviewed and selected from numerous submissions. Computational Biology is a wide and varied discipline, incorporating aspects of statistical analysis, data structure and algorithm design, machine learning, and mathematical modeling toward the processing and improved understanding of biological data. Experimentalists now routinely generate new information on such a massive scale that the techniques of computer science are needed to establish any meaningful result. As a consequence, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.
This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, held in Mlaga, Spain, in April 2012 co-located with the Evo* 2012 events. The 15 revised full papers presented together with 8 poster papers were carefully reviewed and selected from numerous submissions. Computational Biology is a wide and varied discipline, incorporating aspects of statistical analysis, data structure and algorithm design, machine learning, and mathematical modeling toward the processing and improved understanding of biological data. Experimentalists now routinely generate new information on such a massive scale that the techniques of computer science are needed to establish any meaningful result. As a consequence, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.
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