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Titlebook: Artificial Immune Systems; Third International Giuseppe Nicosia,Vincenzo Cutello,Jon Timmis Conference proceedings 2004 Springer-Verlag Be

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Online Negative Databasesing have the potential for an extra security feature in which the “normal” profile of a system is hidden from its possible hijackers. Even if the model of normal behavior falls into the wrong hands, reconstructing the set of valid or “normal” strings is an .-hard problem. The data-hiding aspects of
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Definition of MHC Supertypes Through Clustering of MHC Peptide Binding Repertoiresecognition. Identification of these antigenic peptides is especially important for developing peptide-based vaccines. Consequently experimental and computational approaches have been developed for their identification. A major impediment to such an approach is the extreme polymorphism of HLA, which
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Integration of Immune Models Using Petri Netsrom spreading in host and to clear them effectively. To achieve those mechanisms, particular processes, such as clonal expansion, positive and negative selection, and somatic hypermutation and so on, have been evolved. These properties inspired people to open a new field, called artificial immune sy
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MHC Class I Epitope Binding Prediction Trained on Small Data Setst vaccines, and for epitope/peptide vaccines as such. The highly diverse MHC class I alleles bind very different peptides, and accurate binding prediction methods exist only for alleles were the binding pattern have been deduced from peptide motifs. Using empirical knowledge of important anchor posi
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Negative Selection Algorithm for Aircraft Fault Detectioncted under normal and various simulated failure conditions) using the NASA Ames man-in-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.
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