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Fuzzy Systems in Bioinformatics and Computational Biology by Yaochu Jin (English
US $205.18
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Located in: Fairfield, Ohio, United States
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eBay item number:365904436343
Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- ISBN-13
- 9783540899679
- Book Title
- Fuzzy Systems in Bioinformatics and Computational Biology
- ISBN
- 9783540899679
About this product
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3540899677
ISBN-13
9783540899679
eBay Product ID (ePID)
71614714
Product Key Features
Number of Pages
Xvi, 332 Pages
Publication Name
Fuzzy Systems in Bioinformatics and Computational Biology
Language
English
Subject
Engineering (General), Cad-Cam, Logic, Applied
Publication Year
2009
Type
Textbook
Subject Area
Mathematics, Computers, Technology & Engineering
Series
Studies in Fuzziness and Soft Computing Ser.
Format
Hardcover
Dimensions
Item Weight
26.5 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
Series Volume Number
242
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
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 Scale Biology.- Fuzzy C-Means Techniques for Medical Image Segmentation.- Monitoring and Control of Anesthesia Using Multivariable Self-Organizing Fuzzy Logic Structure.- Interval Type-2 Fuzzy System for ECG Arrhythmic Classification.- Fuzzy Logic in Evolving in silico Oscillatory Dynamics for Gene Regulatory Networks.
Synopsis
Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties. 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 data classification and anesthesia monitoring and control. This volume is a valuable reference for researchers, practitioners, as well as graduate students working in the field of bioinformatics, biomedical engineering and computational biology., Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties. 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 data classification and anesthesia monitoring and control. This volume is a valuable reference for researchers, practitioners, as well as graduate students working in the field of bioinformatics, biomedical engineering and computational biology., 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 Scale Biology.- Fuzzy C-Means Techniques for Medical Image Segmentation.- Monitoring and Control of Anesthesia Using Multivariable Self-Organizing Fuzzy Logic Structure.- Interval Type-2 Fuzzy System for ECG Arrhythmic Classification.- Fuzzy Logic in Evolving in silico Oscillatory Dynamics for Gene Regulatory Networks., Biological systems are inherently stochastic and uncertain. This book shows how fuzzy logic, a powerful tool in capturing uncertainties in engineering systems, has in recent years become popular in analyzing biological data and modeling biological systems.
LC Classification Number
TA345-345.5
Item description from the seller
Seller feedback (1,065,626)
- 3***4 (307)- Feedback left by buyer.Past monthVerified purchaseBook as described, shipped ontime, decent value.
- 3***4 (307)- Feedback left by buyer.Past monthVerified purchaseBook as described, shipped ontime, decent value.
- i***r (3)- Feedback left by buyer.Past monthVerified purchasecover was creased slightly upon delivery, still in very good condition. paper back as promised, good quality & i paid half of what i would’ve paid in the bookstore.
Seller feedback (1,065,626)
- 3***4 (307)- Feedback left by buyer.Past monthVerified purchaseBook as described, shipped ontime, decent value.
- 3***4 (307)- Feedback left by buyer.Past monthVerified purchaseBook as described, shipped ontime, decent value.
- i***r (3)- Feedback left by buyer.Past monthVerified purchasecover was creased slightly upon delivery, still in very good condition. paper back as promised, good quality & i paid half of what i would’ve paid in the bookstore.