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Cross reaction antigen computer-aided screening method

A computer-aided, cross-reactive technology, applied in computing, special data processing applications, instruments, etc., can solve the problems of no obvious improvement and low prediction efficiency.

Inactive Publication Date: 2007-01-03
SHANGHAI JIAO TONG UNIV
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AI Technical Summary

Problems solved by technology

There are relevant literatures on the prediction of B cell linear epitopes, but most of the prediction methods are based on a single amino acid scale or a simple combination of several amino acid scales, and the prediction efficiency is very low
Martin J.Blythe et al., in "Protein Science" Vo1.14, 2005, 246-248 (Protein Science, Volume 14, Pages 246-268, 2005), on the AAindex484 scales and their combinations to the existing B Cell epitope prediction methods were evaluated, and it was found that these methods did not significantly improve

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Embodiment Construction

[0020] Such as figure 1 As shown, computer-aided screening of cross-reactive antigens between pathogenic microorganisms and human specific tissue cells requires five steps:

[0021] 1. Establish a data set of pathogenic microorganisms and human-specific tissue cells

[0022] The Swiss-Prot protein database can be downloaded from the server of Peking University, address: ftp: / / cn.expasy.org / . The condition for searching all proteins of a certain pathogenic microorganism is: OG=English name of pathogenic microorganism; searching for all proteins of human-specific tissue cells is: OG=homo sapiens; TissueSpecificity=English name of tissue cells. Convert to FASTA format after searching. All of the above can be realized through perl programming. For human-specific tissue cell proteins, manual screening is required after the search to ensure the correctness of the data set;

[0023] 2. Establish a data set of B cell linear epitopes

[0024] B cell linear epitopes are split into ...

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Abstract

The invention relates to a method to select the cross reacting antigen by the computer auxiliary. It sets the protein data bank of the pathogeny microorganism and the human specific histiocyte, then to get the preset length of the similar subsequence by the local sequence comparing arithmetic; it sets the data bank of the linear epitope and the nonlinear epitope of the B cells to support the training of the SVM which predicts the probability of the linear epitope of the B cells. It selects the big probability of the similar subsequence according to the probability of the linear epitope of the B cells. The invention has decreased the experiment workload for the immunologist.

Description

technical field [0001] The invention relates to a method in the field of computer application technology, in particular to a method for computer-aided screening of cross-reactive antigens between pathogenic microorganisms and human tissue cells. Background technique [0002] Immune cross-reactivity refers to the ability of antibodies induced by one antigen to react with another different antigen. These two antigens are called cross-reactive antigens. Many human diseases are caused by cross-reactive antigens between pathogenic microorganisms and human specific tissue cells. For example, after certain strains of Streptococcus cause infection (rheumatic fever), antibodies against the myocardium and endocardium may appear, thereby causing damage to the myocardium and endocardium. Discovering the cross-reactive antigens of pathogenic microorganisms is of great significance for elucidating the pathogenic mechanism of pathogenic microorganisms and formulating control measures. On...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 陈军杨杰刘蕙
Owner SHANGHAI JIAO TONG UNIV
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