Buch, Englisch, Band 94, 326 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 682 g
Buch, Englisch, Band 94, 326 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 682 g
Reihe: Studies in Computational Intelligence
ISBN: 978-3-540-76802-9
Verlag: Springer Berlin Heidelberg
Bioinformatics involve the creation and advancement of algorithms using techniques including computational intelligence, applied mathematics and statistics, informatics, and biochemistry to solve biological problems usually on the molecular level. Major research efforts in the field include sequence analysis, gene finding, genome annotation, protein structure alignment analysis and prediction, prediction of gene expression, protein-protein docking/interactions, and the modeling of evolution.
This book deals with the application of computational intelligence in bioinformatics. Addressing the various issues of bioinformatics using different computational intelligence approaches is the novelty of this edited volume.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Naturwissenschaften Biowissenschaften Biowissenschaften
Weitere Infos & Material
Computational Intelligence Algorithms and DNA Microarrays.- Inferring Gene Regulatory Networks from Expression Data.- Belief Networks for Bioinformatics.- Swarm Intelligence Algorithms in Bioinformatics.- Time Course Gene Expression Classification with Time Lagged Recurrent Neural Network.- Tree-Based Algorithms for Protein Classification.- Covariance-Model-Based RNA Gene Finding: Using Dynamic Programming versus Evolutionary Computing.- Fuzzy Classification for Gene Expression Data Analysis.- Towards the Enhancement of Gene Selection Performance.- Saccharomyces pombe and Saccharomyces cerevisiae Gene Regulatory Network Inference Using the Fuzzy Logic Network.- Multivariate Regression Applied to Gene Expression Dynamics.- The Amine System Project: Systems Biology in Practice.- DNA Encoding Methods in the Field of DNA Computing.
