Fuzzy systems in bioinformatics and computationalbiology

Fuzzy systems in bioinformatics and computationalbiology

Jin, Y.
Wang, L.

152,83 €(IVA inc.)

Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and analysis approaches are also becoming popular in analyzing biological data and modeling biological systems. Numerous research and application results have been reported that demonstrated the effectiveness of fuzzy logic in solving a wide range of biological problems found in bioinformatics, biomedical engineering, and computational biology. Contributed by leading experts world-wide, this edited book contains 16 chapters presenting representative research results on the application of fuzzy systems to genome sequence assembly, gene expression analysis, promoter analysis, cis-regulation logic analysis and synthesis, reconstruction of genetic and cellular networks, as well as biomedical problems, such as medical image processing, electrocardiogram dataclassification and anesthesia monitoring and control. Presents the latest trends in bioinformatics, bioengineering and computational biology INDICE: From the contents Induction of Fuzzy Rules by Means of Artificial Immune Systems in Bioinformatics.- Fuzzy Genome Sequence Assembly for Single and Environmental Genomes.- A Hybrid Promoter Analysis Methodology for Prokaryotic Genomes.- Fuzzy Vector Filters for cDNA Microarray Image Processing.- Microarray Data Analysis Using Fuzzy Clustering Algorithms.- Fuzzy Patterns and GCS Networks to Clustering Gene Expression Data.- Gene Expression Analysis by Fuzzy and Hybrid Fuzzy Classification.- Detecting Gene Regulatory Networks from Microarray Data using Fuzzy Logic.- Fuzzy System Methods in Modeling Gene Expression and Analyzing Protein Networks.- Evolving a Fuzzy Rulebase to Model Gene Expression.- Infer Genetic / Transcriptional Regulatory Networks by Recognition of Microarray Gene Expression Patterns using Adaptive Neuro-Fuzzy Inference Systems.- Scalable Dynamic Fuzzy Biomolecular Network Models for Large ScaleBiology.- Fuzzy C-means Techniques for Medical Image Segmentation.

  • ISBN: 978-3-540-89967-9
  • Editorial: Springer
  • Encuadernacion: Cartoné
  • Páginas: 345
  • Fecha Publicación: 01/01/2009
  • Nº Volúmenes: 1
  • Idioma: Inglés