摘要
Microarraytechnologycanbeemployedtoquantitativelymeasuretheexpressionofthousandsofgenesinasingleexperiment.Ithasbecomeoneofthemaintoolsforglobalgeneexpressionanalysisinmolecularbiologyresearchinrecentyears.Thelargeamountofexpressiondatageneratedbythistechnologymakesthestudyofcertaincomplexbiologicalproblemspossible,andmachinelearningmethodsareexpectedtoplayacrucialroleintheanalysisprocess.Inthispaper,wepresentourresultsfromintegratingtheself-organizingmap(SOM)andthesupportvectormachine(SVM)fortheanalysisofthevariousfunctionsofzebrafishgenesbasedontheirexpression.Themostdistinctivecharacteristicofourzebrafishgeneexpressionisthatthenumberofsamplesofdifferentclassesisimbalanced.WediscusshowSOMcanbeusedasadata-filteringtooltoimprovetheclassificationperformanceoftheSVMonthisdataset.
出版日期
2005年02月12日（中国期刊网平台首次上网日期，不代表论文的发表时间）
