于化龙等:基于相关性分析的微阵列数据集成分类研究
335
[173
[18]
Gunn
S
R.Support
vector
machinesforclassificationand
regression[EB/OL].(1998-05-10)[2008—11—23].httpi//users.ecs.soton.ac.uk/srg/publications/pdflSVM.pdf
Wang
Y
H,Makedon
F
S,FordJC。eta1.HykGene:A
hybrid
approachfor
selectingmarkergenes
forphenotype
classification
using
microarray
genc
expression
data口].
Bioinformatics,2005,21(8):1530—1537
Yu
Hualong,bornin
1982.Receivedhis
masterdegree
in
computer
sciencefrom
Harbin
Engineering
University
in
2008.
Heiscurrently
a
PhDcandidateofHarbinEngineeringUniversity.Student
member
ofChina
Computer
Federation.His
current
research
interestsmainly
include
bioinformatics,patternrecognition
andmachinelearning.
于化龙,1982年生。博士研究生,中国计算机学会学生会员,主要研究方向为生物信息学、模式识别与机器学习.
GuGuochang。bornin1946.ProfessorandPhDsupervisoroftheCollegeofComputer
Science
and
Technology。
Harbin
EngineeringUniversity,Harbin,China.
Hismainresearchinterestsinelude
pattern
recognition.mxageprocessing,
machine
learning
and
bioinformaticS.
顾国昌,1946年生,教授,博士生导师,主要研究方向为模式识别、图像处理、机器学习与生物信息学.
Liu
Haibo,born
in1976.PhD
and
associate
professor.Hismain
research
interests
include
image
processing
and
pattern
recognition.
刘海波,1976年生,博士,副教授,主要研
究方向为图像处理与模式识别.
Shen
Jing,born
in1969.PhDand
associate
professor.
Her
盐in
research
interestsincludeimage
processinganddata
mining.
沈■。1969年生,博士,副教授,主要研
究方向为图像处理与数据挖掘.
zlh钟Jing?born
in1972.PhD
and
associateprofessor.Hermain
researchinterests
include
software
testing,
softwarereliabilityevaluationandmachine
learning.
赵靖,1972年生,博士,副教授,主要研究方向为软件测试、软件可靠性评估与机器学习.
ResearchBackground
This
workis
partiallysupportedby
National
NaturalScienceFoundationof
China
under
grant
No.60873036,China
PostdoctoralScienceFoundation
Funded
ProjectundergrantNo.20060400809andtheScienceandTechnology
Special
FoundationforYoungResearchersofHeilongjiangProvinceofChinaundergrantNo.QC06C022.
Microarrayis
a
novelbiologytechnologyanditprovidestheability
tO
measuretheexpressionlevelsofthousandsof
genes
simultaneouslyin
a
singleexperimentandmakesitpossible
to
providediagnosisfordisease,especiallyfortumor,atmolecular
level.However,italso
presentschallengefortraditionaldataanalysismethodsandpatternclassificationmethodsbecausethere
area
largenumber
of
gene
expressionvalues
per
experiment,and
a
relatively
small
number
of
experiments.Therefore,
researchershavebeenmoreinterestedinensembleclassificationalgorithmwithbetterperformance.Inthispaper,wepropose
a
novelensembleclassification
algorithm
of
microarray
data
based
on
correlationanalysis
to
solvethe
problems
oflow
classification
accuracy
andexcessivecomputationofthe
current
ensembleclassificationalgorithms,andapplythealgorithm
tO
LeukemiamicroarraydatasetandcolontumordatasettO
validateitsfeasibilityandeffectiveness.Thisworkisexpected
tO
help
medicineresearchersanddoctorstO
design
an
accurate,fast
andlow
storage
tumorclinical
diagnostic
systembased
on
microarraydatainthe
near
future.
基于相关性分析的微阵列数据集成分类研究
作者:于化龙, 顾国昌, 刘海波, 沈晶, 赵靖, Yu Hualong, Gu Guochang, Liu Haibo,Shen Jing, Zhao Jing
作者单位:哈尔滨工程大学计算机科学与技术学院,哈尔滨,150001
刊名:
计算机研究与发展
英文刊名:JOURNAL OF COMPUTER RESEARCH AND DEVELOPMENT
年,卷(期):2010,47(2)
被引用次数:2次
参考文献(18条)
1.Alon U;Barkai N;Notterman D A Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide array 1999(12)
2.Golub T R;Slonim D K;Tamayo P Molecular classification of cancer:class discovery and class prediction by gene expression monitoring[外文期刊] 1999(5439)
3.Guyon I;Weston J;Barnhill S Gene selection for cancer classification using support vector machines [外文期刊] 2002(01)
4.Dettling M Bagboosting for tumor classification with gene expression data[外文期刊] 2004(18)
5.Bertoni A;Folgieri R;Valentini G Bio-molecular cancer prediction with random subspace ensembles of support vector machines[外文期刊] 2005(01)
6.Hu H;Li J Y;Wang H A maximally diversified multiple decision tree algorithm for microarray data classification 2007
7.Peng Y H A novel ensemble machine learning for robust microarray data classification[外文期刊] 2006(06)
8.Kim K J;Cho S B An evolutionary algorithm approach to optimal ensemble classifiers for DNA microarray data analysis[外文期刊] 2008(03)
9.Chen Y H;Zhao Y O A novel ensemble of classifiers for microarray data classification 2008(04)
10.Krogh A;Vedelsby J Neural network ensembles,cross validation,and active learning 1995
11.Zhou Z H;Wu J X;Tang W Ensembling neural networks:Many could be better than all[外文期刊]
2002(01)
12.Xing E P;Jordan M I;Karp R M Feature selection for high-dimensional genomic microarray data[外文会议] 2001
13.Roth F P Bringing out the best features of expression data 2001(11)
14.李颖新;阮晓钢基于支持向量机的肿瘤分类特征基因选取[期刊论文]-计算机研究与发展 2005(10)
15.王树林;王戟;陈火旺肿瘤信息基因启发式宽度优先搜索算法研究[期刊论文]-计算机学报 2008(04)
16.Inza I;Larranaga P;Blanco R Filter versus wrapper gene selection approaches in DNA microarray domains[外文期刊] 2004(02)
17.Gunn S R Support vector machines for classification and regression 2008
18.Wang Y H;Makedon F S;Ford J C HykGene:A hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data[外文期刊] 2005(08)
1.杨善秀.韩飞.关健基于聚类和微粒群优化的基因选择新方法[期刊论文]-计算机应用 2013(5)
2.于化龙.高尚.赵靖.秦斌基于过采样技术和随机森林的不平衡微阵列数据分类方法研究[期刊论文]-计算机科学2012(5)
本文链接:https://www.wendangku.net/doc/5f17508807.html,/Periodical_jsjyjyfz201002016.aspx