Fuzzy Systems in Bioinformatics 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...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2009.
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| Σειρά: | Studies in Fuzziness and Soft Computing,
242 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.
