EPITOPE-PARATOPE RECOGNITION BY KNOWLEDGE BASED CORRELATION MAPPING USING HOPFIELD NETWORK

Rajani   R.   Joshi

doi:10.2174/0929866013409418

Abstract

The knowledge based correlation mapping (KBCM) is devised here as a unified measure of the information on antigen-antibody complexes available in the Protein Data Banks. This mapping is estimated from a random training sample using a Hopfield Network while representing the epitope and paratope in a complex as 3-dimensional attributed graphs. Identification of paratopes on immunoglobulins against given epitopes is carried out using pattern matching on Hopfield Network with the help of the KBCM.

Keywords: EPITOPE-PARATOPE, knowledge based correlation mapping (KBCM), Epitope, Paratope, immunoglobulins

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Protein & Peptide Letters

Title: EPITOPE-PARATOPE RECOGNITION BY KNOWLEDGE BASED CORRELATION MAPPING USING HOPFIELD NETWORK

Volume: 8 Issue: 4

Author(s): Rajani R. Joshi

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Keywords: EPITOPE-PARATOPE, knowledge based correlation mapping (KBCM), Epitope, Paratope, immunoglobulins

Abstract: The knowledge based correlation mapping (KBCM) is devised here as a unified measure of the information on antigen-antibody complexes available in the Protein Data Banks. This mapping is estimated from a random training sample using a Hopfield Network while representing the epitope and paratope in a complex as 3-dimensional attributed graphs. Identification of paratopes on immunoglobulins against given epitopes is carried out using pattern matching on Hopfield Network with the help of the KBCM.

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Joshi R. Rajani, EPITOPE-PARATOPE RECOGNITION BY KNOWLEDGE BASED CORRELATION MAPPING USING HOPFIELD NETWORK, Protein & Peptide Letters 2001; 8 (4) . https://dx.doi.org/10.2174/0929866013409418