clonal selection theory

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clonal selection theory

[¦klōn·əl si′lek·shən ‚thē·ə·rē]
(immunology)
Theory to explain the specificity of the adaptive immune response according to which there is a large pool of lymphocytes, each having genetically predetermined specificity for only one of a vast array of possible antigens. Upon encountering an antigen, the lymphocytes sensitive to it reproduce much more rapidly than the others, thus leading to a build-up of antigen-specific cells large enough to mount the response.
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MO (2013), Clonal Selection Algorithm with GEP Code for Function Modeling, Pattern Recognition & Artificial Intelligence, Chinese Association Automation, vol.
The scores were assigned by a technician with 25 years of experience in clonal selection, and mainly reflect plant health, plant architecture, and stem number, diameter and height.
Here, we implement a clonal selection classifier [21,38] to test the diagnosis rate of each feature extraction approach.
This and subsequent studies have enhanced the acceptance of xenografts as models of clonal selection and acquired resistance to therapy.
Clonal selection algorithm (De Castro & Von Zuben, 2000) is used by natural immune system to define the basic features of an immune response to an antigenic stimulus.
In this study, Clonal Selection Algorithm, based on the clonal selection process of the immune system, is applied to optimization of site layouts.
Clonal selection by limiting dilution in semi-solid media was performed with Clone-Matrix semi-solid concentrated and CloneXL Reagent (Genetix, USA) in addition to CD OptiCHO[TM] cloning medium (2x, Invitrogen, USA).
An AIS-based optimization algorithm, called immune clonal selection algorithm[20], which has been widely used in engineering-oriented fields in recent years, such as network routing [21], job scheduling [22][23], image recognition [24][25], multi-user detection [26] and so on.
The principle of clonal selection has its artificial implementation and is used for solving optimisation problems (De Castro, Von Zuben 1999).
To carry out the clonal selection in the process of the development of the upgrade plan, the entire list of works on aeronautical system upgrade, as well as their resource limitations, is formalised as antibodies.
In this section, genetic algorithm will be introduced first followed by the clonal selection algorithm, finally our hybrid genetic-clonal algorithm is proposed.
Some topics covered: artificial clonal selection, biomedical data mining, cat swarm optimization, computational intelligence, fuzzy functional dependencies, hybrid evolutionary learning algorithms, and risk-management models.