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Gene selection approach based on improved swarm intelligent optimisation algorithm for tumour classification

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成果类型:
期刊论文
作者:
Jin, Cong*;Jin, Shu-Wei
通讯作者:
Jin, Cong
作者机构:
[Jin, Cong] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.
[Jin, Shu-Wei] Ecole Normale Super, Dept Phys, 24 Rue Lhomond, F-75231 Paris 5, France.
通讯机构:
[Jin, Cong] C
Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
tumours;swarm intelligence;particle swarm optimisation;pattern classification;medical computing;genetics;gene datasets;ensemble classifiers;tumour classifiers;gene space;informative genes;gene expression profiles;tumour classification;swarm intelligent optimisation algorithm;gene selection approach
期刊:
IET Systems Biology
ISSN:
1751-8849
年:
2016
卷:
10
期:
3
页码:
107-115
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
A number of different gene selection approaches based on gene expression profiles (GEP) have been developed for tumour classification. A gene selection approach selects the most informative genes from the whole gene space, which is an important process for tumour classification using GEP. This study presents an improved swarm intelligent optimisation algorithm to select genes for maintaining the diversity of the population. The most essential characteristic of the proposed approach is that it can automatically determine the number of the selected genes. On the basis of the gene selection, the ...

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