1.

Record Nr.

UNISA996465995003316

Titolo

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics [[electronic resource] ] : 10th European Conference, EvoBIO 2012, Málaga, Spain, April 11-13, 2012, Proceedings / / edited by Mario Giacobini, Leonardo Vanneschi, William S. Bush

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012

ISBN

3-642-29066-3

Edizione

[1st ed. 2012.]

Descrizione fisica

1 online resource (XIII, 255 p. 76 illus.)

Collana

Theoretical Computer Science and General Issues, , 2512-2029 ; ; 7246

Disciplina

570.285

Soggetti

Bioinformatics

Algorithms

Database management

Artificial intelligence

Computer science

Artificial intelligence—Data processing

Computational and Systems Biology

Database Management

Artificial Intelligence

Theory of Computation

Data Science

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and author index.

Sommario/riassunto

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 Málaga, 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.