Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques.
Readership: Postdoctoral fellows, students, senior investigators and professional practitioners/bioinformatics experts. Also used as a textbook for upper undergraduates and graduates in bioinformatics.
Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques.Contents: Introduction to Bioinformatics; Introduction to Fuzzy Set Theory and Fuzzy Logic; Fuzzy Similarities in Ontologies; Fuzzy Logic in Structural Bioinformatics; Microarray Data Analysis; Other Applications; Summary; Fundamental Biological Concepts; Online Resources.
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