Title
Classification Of Diffuse Large B Cell Lymphoma Gene Expression Data Based On Two-Layer Particle Swarm Optimization
Abstract
Classification of gene expression data to determine subtype of samples is meaningful to research tumors in molecular biology level. It is also an important way to make further treatment plan for the patient. Particle swarm optimization (PSO) is proven to be an ineffective solution for classification and clustering in bioinformatics as it could not give a stable prediction result. In this study, a classifier based on the two layer particle swarm optimization (TLPSO) algorithm and uncertain training sample sets is established. Samples of diffuse large B cell lymphoma (DLBLC) gene expression data are used for training and validating. The classification stability and accuracy by the proposed TLPSO algorithm increase significantly compared with the results obtained by using algorithms known as PSO and Kmeans.
Year
DOI
Venue
2013
10.1109/FSKD.2013.6816234
2013 10TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD)
Keywords
Field
DocType
classification, gene, TLPSO, PSO, DLBLC
Particle swarm optimization,Diffuse large B-cell lymphoma,Data mining,Pattern recognition,Computer science,Gene expression,Prediction algorithms,Artificial intelligence,Cluster analysis,Classifier (linguistics),Statistical classification,Machine learning
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Yajie Liu1193.31
xinling shi27415.34
guoliang huang331.88
Baolei Li473.85
Lei Zhao501.01