Probabilistic learning in immune network: Weighted tree matching model
DSpace at IIT Bombay
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Title |
Probabilistic learning in immune network: Weighted tree matching model
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Creator |
JOSHI, RR
KRISHNANAND, K |
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Subject |
antigen-antibody recognition
system |
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Description |
Adaptive learning properties (of clonal selection and affinity maturation) in the immune network model are investigated in this paper under a nonlinear data structural representation of the involved molecules. Weighted trees are constructed to model the multiple paratopes/epitopes on the antibodies/antigens. Parallel computing experiments are carried out for the canonical coding of these trees and the corresponding multiple matching interactions. Our experiments on real data have shown significant results on the cognitive properties of the immune network. These and other computational results are presented along with a discussion of future applications.
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Publisher |
MARY ANN LIEBERT INC PUBL
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Date |
2011-08-18T14:22:59Z
2011-12-26T12:55:47Z 2011-12-27T05:42:32Z 2011-08-18T14:22:59Z 2011-12-26T12:55:47Z 2011-12-27T05:42:32Z 1996 |
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Type |
Article
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Identifier |
JOURNAL OF COMPUTATIONAL BIOLOGY, 3(1), 143-162
1066-5277 http://dx.doi.org/10.1089/cmb.1996.3.143 http://dspace.library.iitb.ac.in/xmlui/handle/10054/10045 http://hdl.handle.net/10054/10045 |
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Language |
en
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