Immune feature recognition method based on neural network

A technology of immune signatures and recognition methods, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as limited funds and time, inability to obtain comprehensive information, inability to obtain information at the molecular level, etc., and achieve cost reduction , the effect of time reduction

Active Publication Date: 2020-07-10
CHENGDU EXAB BIOTECH CO LTD
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Problems solved by technology

[0006] The purpose of the present invention is to propose a neural network-based immune feature recognition method, utilizing the BP neural network to analyze the variable region sequence ( CDR3 sequence) to identify its immune characteristics different from those of the control group, and to solve the problem that existing technologies rely on limited samples. In the case of limited funds and time, only a few indicators can be detected, comprehensive information cannot be obtained, and information at the molecular level cannot be obtained. and other defects, so that a relatively comprehensive characteristic immune information can be identified at the molecular level using a small number of samples

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  • Immune feature recognition method based on neural network
  • Immune feature recognition method based on neural network
  • Immune feature recognition method based on neural network

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[0032] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the implementations shown and described in the drawings are only exemplary, intended to explain the principle and spirit of the present invention, rather than limit the scope of the present invention.

[0033] The embodiment of the present invention provides a neural network-based immune feature recognition method, such as figure 1 As shown, the following steps S1-S5 are included:

[0034] S1. Obtain the CDR3 sequence of the TCR or BCR of the subject and the control group by high-throughput sequencing.

[0035] In the embodiment of the present invention, due to the number of CDR3 sequences (count) of TCR or BCR will be different due to the amount of early sampling (almost the sum of sequence counts is above 50,000), it is necessary to artificially analyze the CDR3 of TCR or BCR of each sample Sequences were randomly s...

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Abstract

The invention discloses an immune feature recognition method based on a neural network. Variable region sequences (CDR3 sequences) of B cell receptors (BCR) or T cell receptors (TCR) of subjects are obtained according to high-throughput sequencing, and are compared with BCR or TCR variable region sequence (CDR3 sequence) set of a control group to obtain immune feature sequences, different from thesequences of the control group, of the individual subjects or a subject group; and immune feature models of the subjects and the control group are constructed by utilizing a feedforward back propagation (BP) neural network algorithm, so the immune features of samples can be identified at a molecular level.

Description

technical field [0001] The invention belongs to the technical field of immune feature identification, and in particular relates to the design of a neural network-based immune feature identification method. Background technique [0002] Identifying the immune characteristics of specific organisms (including but not limited to humans and mammals) individuals or groups relative to the control group is an important and necessary detection in biological and medical research. Existing detection methods mainly include antibody / immune factor detection, blood routine detection, lymphocyte subset analysis, etc. [0003] Among them, the detection of antibodies / immune factors can detect the content of antibodies and / or immune factors such as immunoglobulin, complement, interferon, and interleukin in the blood through enzyme-linked immunosorbent assay (ELISA), fluorescent quantitative PCR test, etc., or detect immune factors. The cells express the level of these antibodies and / or immune...

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Application Information

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IPC IPC(8): G16B30/10G16B40/00G06N3/04G06N3/08
CPCG16B30/10G16B40/00G06N3/084G06N3/045
Inventor 张志新杨鑫卓越
Owner CHENGDU EXAB BIOTECH CO LTD
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