9781420065459

Immunological Computation: Theory and Applications

by ;
  • ISBN13:

    9781420065459

  • ISBN10:

    1420065459

  • Format: Hardcover
  • Copyright: 2008-09-12
  • Publisher: Auerbach Public

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Summary

Clearly, nature has been very effective in creating organisms that are capable of protecting themselves against a wide variety of pathogens such as bacteria, fungi, and parasites. The powerful information-processing capabilities of the immune system, such as feature extraction, pattern recognition, learning, memory, and its distributive nature provide rich metaphors that researchers are finding very useful for the development of computational models. While some of these models are designed to give us a better understanding of the immune system, other models are being developed to solve complex real-world problems such as anomaly detection, pattern recognition, data analysis (clustering), function optimization, and computer security.

Table of Contents

Prefacep. xiii
Acknowledgmentsp. xv
Authorsp. xvii
Immunology Basicsp. 1
Functional Elements of the Immune Systemp. 2
Organsp. 2
Bone Marrowp. 2
Thymusp. 3
Spleenp. 3
Lymph Nodep. 3
Immune Cells and Moleculesp. 3
Lymphocytes, T Lymphocytes, and B Lymphocytesp. 4
Antibodiesp. 5
Cytokines, Lymphokines, and Interleukinsp. 5
Peptides, Major Histocompatibility Complex, and Antigen Presenting Cellsp. 6
Macrophages and Dendritic Cellsp. 7
The Complement Systemp. 7
Layers of the Immune Systemp. 8
Anatomic Barrierp. 8
Innate Immunityp. 8
Adaptive Immunityp. 9
Immune System Dynamicsp. 9
Immune Recognition: Matching and Bindingp. 10
Response to Antigensp. 11
T Cell Maturationp. 12
B Cell Proliferation: Affinity Maturationp. 14
Germinal Centerp. 15
Apoptosis and Lysisp. 17
Circulatory Mechanismp. 18
Regulatory Mechanismsp. 19
Signaling and Message-Passing Mechanismp. 20
Summaryp. 22
Review Questionsp. 22
Referencesp. 24
Theoretical Models of Immune Processesp. 27
Clonal Selection Theoryp. 27
Immune Network Theoryp. 29
First-Generation Immune Networksp. 29
Second-Generation Immune Networksp. 31
Third-Generation Immune Networksp. 32
Multiepitope Immune Networkp. 33
Modeling the Germinal Centerp. 33
Danger Theoryp. 38
Computational Aspects of the Immune Systemp. 40
Summaryp. 41
Review Questionsp. 42
Referencesp. 43
Immunity-Based Computational Modelsp. 45
Shape-Space and Affinityp. 46
Representation Schemesp. 48
Affinity Measuresp. 48
String-Matching Rulesp. 50
Hamming Distancep. 50
Binary Distancep. 50
Edit Distancep. 52
Value Difference Metricp. 52
Landscape-Affinity Matchingp. 53
R-Contiguous Bits Matchingp. 53
R-Chunk Matching Rulep. 54
Real-Valued Vector Matching Rulesp. 54
Euclidean Distancep. 54
Partial (Euclidean) Distancep. 54
Minkowski Distancep. 55
Chebyshev Distancep. 55
Mixed Representationp. 55
Heterogeneous Euclidean-Overlap Metricp. 55
Heterogeneous Value Difference Metricp. 56
Considerations about Representationp. 56
Affinity Maturationp. 57
Solving Problems Applying Immunity-Based Modelsp. 57
Summaryp. 58
Review Questionsp. 58
Referencesp. 59
T Cell-Inspired Algorithmsp. 61
Self/Nonself Discriminationp. 61
Negative Selection Algorithmsp. 62
Negative Detector Generation Schemesp. 64
An Exhaustive Approach (Generating Detectors Randomly)p. 64
A Dynamic Programming Approach (Linear-Time Algorithm)p. 65
Phase I: Solving the Counting Recurrencep. 66
Phase II: Generating Strings Unmatched by Sp. 67
A Greedy Algorithm for Detector Generationp. 69
Other Variants in Detector Generationp. 70
NSMutation Algorithmp. 70
Binary Templatep. 71
DynamiCSp. 72
Schemata-Based Detection Rulesp. 72
Analysis of Negative Selection Algorithmsp. 73
Complexity of Detector Generationp. 73
Immunological Holesp. 74
Empirical Analysis: Binary Matching Rules and Detector Coveragep. 77
Real-Valued Negative Selection Algorithmsp. 79
Detector Generation Using Evolutionary Algorithmsp. 82
Negative Selection with Fuzzy Detection Rulesp. 85
Randomized Approaches in Generating (Fixed Size) Spherical Detectorsp. 88
Estimation of Detector Volume and Overlapp. 90
An Iterative Approach in Generating (Variably Sized) Negative Detectorsp. 92
Testing Processp. 94
A Statistical Method: V-Detector Algorithmp. 95
Multishaped Negative Detector Generationp. 97
Applicability Issues of Real-Valued Negative Selection Algorithmsp. 100
Positive Selection (Detection)p. 101
Negative Databasep. 103
Negative Database Representationp. 103
Representation of Negative Databases as Satisfiability Problemsp. 104
Approaches to Generate Negative Databasesp. 104
Prefix Algorithmp. 105
Randomized Algorithmp. 105
Operations on Negative Databasep. 107
Negative Algebrap. 107
Summaryp. 109
Research Questionsp. 111
Review Questionsp. 111
Referencesp. 113
B Cell-Inspired Algorithmsp. 117
Clonal Selection Algorithmsp. 117
Immune Network Modelsp. 120
Continuous Immune Network Modelsp. 123
Jerne's Idiotypical Networkp. 124
Coutinho and Varela's Idiotypical Networkp. 125
Farmer, Packard, and Perelson's Idiotypical Networkp. 125
Parisi's Idiotypical Networkp. 127
Stewart and Carneiro's Idiotypical Networkp. 128
Discrete Immune Network Modelsp. 129
Hunt and Cooke's Immune Network Model and Its Variationp. 129
Fractal Immune Networkp. 130
AiNet and Its Variationsp. 132
Opt-aiNetp. 132
Dynamic Optimization AiNetp. 135
Fuzzy Immune Network Modelp. 139
A General Model of Artificial Immune Networkp. 144
Summaryp. 147
Exercisesp. 149
General Questionsp. 149
Referencesp. 150
Latest Immune Models and Hybrid Approachesp. 153
The Danger Theoryp. 153
Danger Theory-Based Algorithmsp. 155
Combining Dendritic Cells and Danger Theoryp. 159
Multilevel Immune Learning Algorithmp. 160
Major Histocompatibility Complex-Based Systemsp. 162
Cytokine Network Modelp. 162
Phylogenies of T Cellsp. 164
Combining Negative Selection and Classification Techniquesp. 165
Summaryp. 167
Review Questionsp. 167
Referencesp. 168
Real-World Applicationsp. 171
Solving Problems Using Immunological Computationp. 171
Applications in Computer Securityp. 172
Virus Detectionp. 172
An Alternative Approach to Virus Detectionp. 173
UNIX Process Monitoringp. 175
Immunity-Based Intrusion Detection Systemsp. 176
Immune Agent Architecturep. 178
Immunogenetic Approaches in Intrusion Detectionp. 178
Danger Theory in Network Securityp. 179
Dendritic Cell Algorithmp. 179
TLR Algorithmp. 179
Applications in Fraud Detectionp. 182
Application in Robotics and Controlp. 183
Application in Fault Detection and Diagnosisp. 185
Application to Schedulingp. 188
AIS in Data Miningp. 189
Applications in Web Miningp. 190
Application in Anomaly Detectionp. 190
Solving Optimization Problemsp. 192
Other Applicationsp. 193
Developing Associative Memoriesp. 193
Applications in Gamesp. 193
Applications in Software Testingp. 194
Hybrid Approachesp. 195
Application in Neural Networksp. 195
Applications in Genetic Algorithmsp. 195
Summaryp. 196
Review Questionsp. 197
Referencesp. 198
Indexed Bibliographyp. 205
Indexp. 269
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