Contents -- Foreword -- Preface -- 1. Introduction to Bioinformatics -- 1.1 What Is Bioinformatics -- 1.2 A Brief History of Bioinformatics -- 1.3 Scope of Bioinformatics. -- 1.4 Major Challenges in Bioinformatics -- 1.5 Bioinformatics and Computer Science -- 2. Introduction to Fuzzy Set Theory and Fuzzy Logic -- 2.1 Where Does Fuzzy Logic Fit in Computational Science? -- 2.2 Why Do We Need to Use Fuzziness in Biology? -- 2.3 Brief History of the Field. -- 2.4 Fuzzy Membership Functions and Operators. -- 2.4.1 Membership functions -- 2.4.2 Basic fuzzy set operators. -- 2.4.3 Compensatory operators. -- 2.5 Fuzzy Relations and Fuzzy Logic Inference. -- 2.6 Fuzzy Clustering -- 2.6.1 Fuzzy C-Means -- 2.6.2 Extension to fuzzy C-Means. -- 2.6.3 Possibilistic C-Means (PCM) -- 2.7 Fuzzy K-Nearest Neighbors -- 2.8 Fuzzy Measures and Fuzzy Integrals. -- 2.8.1 Fuzzy measures. -- 2.8.2 Fuzzy integrals -- 2.9 Summary and Final Thoughts -- 3. Fuzzy Similarities in Ontologies. -- 3.1 Introduction -- 3.2 Definition of Ontology-Based Similarity -- 3.3 Set-Based Similarity Measure. -- 3.3.1 Pair-wise aggregation. -- 3.3.2 Bag of words similarities. -- 3.4 Fuzzy Measure Similarity -- 3.5 Fuzzy Measure Similarity for Augmented Sets of Ontology Objects. -- 3.6 Choquet Fuzzy Integral Similarity Measure. -- 3.7 Examples and Applications of Fuzzy Measure Similarity Using GO Terms -- 3.7.1 Lymphoma case study -- 3.7.2 Gene clustering using Gene Ontology annotations. -- 3.7.3 Gene summarization using Gene Ontology terms. -- 3.8 Ontology Similarity in Data Mining -- 3.9 Discussion and Summary. -- 4. Fuzzy Logic in Structural Bioinformatics -- 4.1 Introduction -- 4.2 Protein Secondary Structure Prediction. -- 4.3 Protein Solvent Accessibility Prediction. -- 4.4 Protein Structure Matching Using Fuzzy Alignments -- 4.5 Protein Similarity Calculation Using Fuzzy Contact Maps.

4.6 Protein Structure Class Classification -- 4.7 Summary. -- 5. Application of Fuzzy Logic in Microarray Data Analyses. -- 5.1 Introduction -- 5.1.1 Microarray data description -- 5.1.2 Microarray processing algorithms for gene selection and patient classification. -- 5.1.3 Microarray processing algorithms for gene regulatory network discovery -- 5.2 Clustering Algorithms -- 5.2.1 (Dis)similarity measures for microarray data -- 5.2.2 Fuzzy C-means (FCM) -- 5.2.3 Relational fuzzy C-means -- 5.2.4 Fuzzy co-clustering algorithms -- 5.3 Inferring Gene Networks Using Fuzzy Rule Systems -- 5.4 Discussion and Summary. -- 6. Other Applications. -- 6.1 Overview -- 6.2 Applications in Biological Sequence Analyses -- 6.2.1 Protein sequence comparison -- 6.2.2 Application in sequence family classification -- 6.2.3 Application in motif identification. -- 6.2.4 Application in protein subcellular localization prediction. -- 6.2.5 Genomic structure prediction -- 6.3 Application in Computational Proteomics -- 6.3.1 Electrophoresis analysis. -- 6.3.2 Protein identification through mass-spec -- 6.4 Application in Drug Design. -- 6.5 Discussion and Summary. -- 7. Summary and Outlook -- Appendix I. Fundamental Biological Concepts -- AI.1 DNA, RNA and Genome. -- AI.1.1 DNA (deoxyribonucleic acid) -- AI.1.2 RNA (ribonucleic acid). -- AI.1.3 Genome -- AI.2 Protein and Its Structure -- AI.3 Central Dogma of Biology -- Appendix II. Online Resources. -- AII.1 Online Resources for Molecular Biology -- AII.2 Online Resources for Bioinformatics -- AII.2.1 Protein structure -- AII.2.1.1 Protein structure database -- AII.2.1.2 Protein structure visualization. -- AII.2.2 Microarray -- AII.2.2.1 Microarray databases -- AII.2.2.2 Microarray analysis tool. -- AII.2.3 Gene ontology. -- AII.2.4 Online portals for bioinformatics.

AII.3 Online Resources for Fuzzy Set Theory and Fuzzy Logic. -- Bibliography -- Index.