Group intelligent optimization based lung cancer cell detector

A cancer cell and detector technology, applied in instruments, biochemical instruments, measuring devices, etc., can solve problems such as difficult to search for the optimal feature subset classification and optimal parameters of gene microarray data

Inactive Publication Date: 2018-10-30
ZHEJIANG UNIV
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Problems solved by technology

[0003] In order to overcome the deficiency that it is currently difficult to search for the optimal feature subset of gene microarray data and th...

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  • Group intelligent optimization based lung cancer cell detector
  • Group intelligent optimization based lung cancer cell detector
  • Group intelligent optimization based lung cancer cell detector

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Embodiment Construction

[0054] The present invention will be described in detail below according to the accompanying drawings.

[0055] refer to figure 1 , a lung cancer cancer cell detector with swarm intelligence optimization, the system consists of a gene microarray read-in module 1, a data preprocessing and feature sorting module 2, a parameter optimization module 3, and a model output module 4; wherein:

[0056] The gene microarray read-in module 1 reads in the category labels of all gene microarrays Y=[y 1 ,y 2 ,...,y m ], where y i =k,k∈(-1,1), and the gene microarray expression values ​​of all samples:

[0057]

[0058] where each line x i Represents the expression values ​​of all genes in a sample, corresponding to each column x j Represents the expression value of a gene in all samples, the subscript i indicates the i-th sample, a total of m, and the subscript j indicates the j-th gene, a total of n.

[0059] The data preprocessing and feature sorting module 2 is the process of no...

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Abstract

The invention discloses a group intelligent optimization based lung cancer cell detector. The system is composed of a gene microarray read-in module, a data preprocessing and feature ordering module,a parameter optimization module and model output. The operating method of the system comprises the following steps: preprocessing the input gene microarray data, erasing noise and performing normalization; performing importance ranking on various residual genes, calculating the correlation by virtue of statistical fraction, calculating the contribution degree by utilizing a classifier criterion function, and ranking importance of all the genes. According to the improved optimization method, adaptability detection and population disturbance are added under an original intelligent optimization algorithm, and the population diversity loss and optimization process can be prevented from running into partial optimization. The searched optimal parameters serve as classifier parameters to completemodel building and output results. The system has excellent de-correlation property and high accuracy.

Description

technical field [0001] The invention relates to the technical field of application of gene microarray data, in particular to a lung cancer cell detector for swarm intelligence optimization. Background technique [0002] The prototype of the gene chip (genechip) (also known as DNA chip, biochip) was proposed in the mid-1980s. The sequencing principle of the gene chip is the method of hybridization sequencing, that is, the method of determining the nucleic acid sequence by hybridizing with a set of nucleic acid probes of known sequence, and the probe of the target nucleotide with known sequence is immobilized on the surface of a substrate. However, how to study the functions of so many genes in the life process has become a common topic for life science workers all over the world. Therefore, it is extremely important to establish new hybridization and sequencing methods to efficiently and quickly detect and analyze a large amount of genetic information. Lung cancer is one of...

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Application Information

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IPC IPC(8): C12M1/34
CPCG01N33/5005
Inventor 刘兴高高信腾孙元萌
Owner ZHEJIANG UNIV
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