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个人简介

一、个人简介 代志军,男,1986年4月出生,博士,讲师,硕士生导师,美国密西根州立大学博士后,湖南农业大学第四批“1515”学术骨干人才,中国致公党员。植物保护学院生物信息系专任教师,主要承担生物统计学、R语言、科技论文写作等课程的教学。主要从事全基因组选择、肿瘤分类与信息基因筛选、药物分子定量构效关系建模、蛋白质相互作用预测、害虫预测预报等研究。 二、教育背景 2017/08–2019/01美国密歇根州立大学,数量遗传学与基因组学课题组,博士后研究学者 2011/09–2014/12湖南农业大学,农业昆虫与害虫防治专业(生物信息学方向),博士 2008/09–2011/06湖南农业大学,生物信息学专业,硕士 2004/09–2008/06湖北工程学院,生物科学专业,学士 三、成果介绍 1.主持的主要科研项目 1)国家自然科学基金青年基金,31701164,基于变量选择与训练群体优化的植物基因组选择方法研究,2018/01-2020/12 2)湖南省自然科学基金青年基金,2018JJ3238,水稻数量性状全基因组选择新方法及应用,2018/01-2020/12 3)作物种质创新与资源利用国家重点实验室培育基地开放项目,15KFXM11,基于最大互信息系数与直接分类的水稻蛋白质相互作用预测,2016/04-2018/03 4)湖南省教育厅科学研究一般项目,16C0776,方差分析与直接分类用于RNA-seq癌基因表达分析,2016/09-2018/12 5)湖南农业大学青年科学基金,16QN33,高维特征选择与直接分类用于癌症差异甲基化研究,2016/09-2018/12 6)中国农学会教育教学类科研课题,PCE1606,“互联网+农业”新引擎助力创新创业教育改革,2016/11-2018/12。主要获奖成果 1)2016年“华为杯”第十三届全国研究生数学建模竞赛二等奖(指导老师) 2)2016年湖南省自然科学奖三等奖(排名4) 3)2015年湖南省首届研究生数学建模竞赛三等奖(指导老师) 4)2014年第十届北美校友奖学金 5)2014年湖南农业大学科研成就奖一等奖 6)2013年湖南省优秀硕士学位论文奖

近期论文

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2019 23)LifengWang,PengweiXing,CongWang,XiaomaoZhou,ZhijunDai*,LianyangBai*.MaximalInformationCoefficientandSupportVectorRegressionBasedNonlinearFeatureSelectionandQSARModelingonToxicityofAlcoholCompoundstoTadpolesofRanatemporaria.JBrazilChemSoc,2019,30(2):279-285. 2018 22)QianXu,LiXiao,LiZeng,ZhijunDai*,YingWu*.PediatricburnsinSouthCentralChina:anepidemiologicalstudy.IntJClinExpMed,2018,11(9):9280-9287. 2017 21)XueliZhang#,CongweiSun#,ZhengZhang,ZhijunDai,YuanChen,XiongYuan,ZhemingYuan,WenbangTang,LanzhiLi*,ZhongliHu.GeneticdissectionofmainandepistaticeffectsofQTLbasedonaugmentedtripletestcrossdesign.PLOSONE,2017,12(12):e0198054. 20)ZhengZhang,XueliZhang,BochengMo,ZhijunDai,ZhongliHu,LanzhiLi*,XingfeiZheng*.CombiningAbilityAnalysisofAgronomicTraitinIndica×IndicaHybridRice.ActaAgronomicaSinica,2017,43(10):1448-1457.(张征,张雪丽,莫博程,代志军,胡中立,李兰芝*,郑兴飞*.籼型杂交水稻农艺性状的配合力研究[J].作物学报,2017,43(10):1448-1457.[CSCD收录]) 2016 19)WeiZhou,YanjunFan,XunhuiCai,YanXiang,PengJiang,ZhijunDai,YuanChen,SiqiaoTan,ZhemingYuan*.High-accuracyQSARmodelsofnarcosistoxicitiesofphenolsbasedonvariousdatapartition,descriptorselectionandmodellingmethods.RSCAdvances,2016,6(108):106847-106855. 2015 18)WeiZhou#,ShuboWu#,ZhijunDai#,YuanChen,YanXiang,JianrongChen,CongweiSun,QingmingZhou*,ZhemingYuan*.NonlinearQSARmodelswithhigh-dimensionaldescriptorselectionandSVRimprovetoxicitypredictionandevaluationofphenolsonPhotobacteriumphosphoreum.ChemometrIntellLab,2015,145,30-38. 17)CongweiSun#,ZhijunDai#,HongyanZhang,LanzhiLi*,andZhemingYuan*.BinaryMatrixShufflingFilterforFeatureSelectioninNeuronalMorphologyClassification.ComputMathMethodM,2015,ArticleID626975,9pages. 16)LiYang,CongweiSun,ZhijunDai,MiaoHe,ZhemingYuan*.ExpansionoftheMolecularNetworkRelatedtoPetalDevelopmentBasedonMADS-boxProteinsandProtein-ProteinInteractionNetworkinArabidopsisthaliana.ChinBullBot,2015,50(5):614-622.(杨黎,孙丛苇,代志军,何淼,袁哲明*.基于MADS-box诱饵与蛋白质相互作用的拟南芥花瓣发育分子网络拓展[J].植物学报,2015,50(05):614-622.[CSCD收录]) 2014 15)ZhijunDai,LifengWang,YuanChen,HaiyanWang,LianyangBai,ZhemingYuan*.ApipelineforimprovedQSARanalysisofpeptides:physiochemicalpropertyparameterselectionviaBMSF,near-negighborsampleselectionviasemivariogram,andweightedSVRregressionandprediction.AminoAcids,2014,46(4):1105-1119. 14)LifengWang#,ZhijunDai#,HongyanZhang,LianyangBai,ZhemingYuan*.QuantitativeSequence-ActivityModelAnalysisofOligopeptidesCouplinganImprovedHigh-DimensionFeatureSelectionMethodwithSupportVectorRegression.ChemBiolDrugDes,2014,83(4):379-391. 13)KaiWang,LifengWang,ZhijunDai,LianyangBai,ZhemingYuan*.QSARmodelingofE.colipromoterswithparametersselectedbybinarymatrixshufflingfilter.J.IndianChemSoc,2014,91(12):2247-2253. 12)YongLi,WeiZhou,ZhijunDai,YuanChen,ZhimingWang,ZhemingYuan*.PredictingtheProteinFoldingRateBasedonSequenceFeatureScreeningandSupportVectorRegression.ActaPhys-Chim.Sin.2014,30(6):1091-1098.(李咏,周玮,代志军,陈渊,王志明,袁哲明*.基于序列特征筛选与支持向量回归预测蛋白质折叠速率[J].物理化学学报,2014,30(06):1091-1098.[SCI收录]) 11)JinghuaLiang,CongweiSun,ZhijunDai,LiYang,ZhemingYuan*.Nonlinearquantitativestructure-activityrelationshipofamidemosquitorepellent.ChineseJournalofPesticideScience,2014,16(6):644-650.(梁景华,孙丛苇,代志军,杨黎,袁哲明*.酰胺类驱蚊剂的非线性定量构效关系[J].农药学学报,2014,16(06):644-650.[CSCD收录]) 10)HongyanZhang,LanzhiLi,ChaoLuo,CongweiSun,YuanChen,ZhijunDai,ZhemingYuan*.InformativeGeneSelectionandDirectClassificationofTumorBasedonChi-SquareTestofPairwiseGeneInteractions.BiomedResInt,2014,ArticleID589290,9pages. 2013 9)WeiZhou,ZhijunDai,YuanChen,ZhemingYuan*.ComputationalQSARmodelswithhigh-dimensionaldescriptorselectionimproveantitumoractivitydesignofARC-111analogues.MedChemRes,2013,22(1):278-286. 8)HaiyanWang,HongyanZhang,ZhijunDai,MingshunChen,ZhemingYuan*.TSG:anewalgorithmforbinaryandmulti-classcancerclassificationandinformativegenesselection.BMCMedGenomics,2013,6(Suppl1):S3. 7)LanzhiLi,CongweiSun,YuanChen,ZhijunDai,ZhenQu,XingfeiZheng,SibinYu,TongminMou,ChenwuXu*,ZhongliHu*.QTLmappingforcombiningabilityindifferentpopulation-basedNCIIdesigns:asimulationstudy.JGenet,2013,92(3):529-543. 6)NaHan,ZhemingYuan*,YuanChen,ZhijunDai,ZhimingWang.PredictionofHLA-A*0201RestrictedCytotoxicTLymphocyteEpitopesBasedonHigh-DimensionalDescriptorNonlinearScreening.ActaPhys.-Chim.Sin.2013,29(9):1945-1953.(韩娜,袁哲明*,陈渊,代志军,王志明.基于高维特征非线性筛选的HLA-A*0201限制性CTL表位预测[J].物理化学学报,2013,29(09):1945-1953.[SCI收录]) 2012 5)WeiZhou#,ZhijunDai#,YuanChen,HaiyangWang,ZhemingYuan*.High-dimensionaldescriptorselectionandcomputationalqsarmodelingforantitumoractivityofarc-111analoguesbasedonsupportvectorregression(SVR).IntJMolSci,2012,13(1):1161-1172. 4)HongyanZhang,HaiyanWang,ZhijunDai,MingshunChen,ZhemingYuan*.Improvingaccuracyforcancerclassificationwithanewalgorithmforgenesselection.BMCbioinformatics,2012,13:298. 3)ManxiuSu,LifengWang,ZhijunDai,ZhemingYuan*,LianyangBai.PrimaryStructuralCharacterizationsofPolypeptideandAntimicrobialPeptidesQSAMModeling.ChemJChineseU,2012,33(11):2526-2531.(苏满秀,王立峰,代志军,袁哲明,柏连阳.多肽一级结构表征与抗菌肽QSAM建模[J].高等学校化学学报,2012,33(11):2526-2531.[SCI收录]) 2011 2)WeiweiLi,ZhijunDai,XianshengTan,ZhemingYuan*.PhenolCompoundsQSARModelingBasedonSupportVectorRegression.ProgModBiomed,2011,11(24):4857-4860.(李巍巍,代志军,谭显胜,袁哲明*.基于支持向量回归的酚类化合物QSAR建模[J].现代生物医学进展,2011,11(24):4857-4860.) 1)ZhijunDai,WeiZhou,ZhemingYuan*.Anovelmethodofnonlinearrapidfeatureselectionforhigh-dimensionalfeaturesanditsapplicationinpeptideQSARmodelingbasedonsupportvectormachine.ActaPhys.-Chim.Sin.2011,27(7):1654-1660.(代志军,周玮,袁哲明*.基于支持向量机的高维特征非线性快速筛选与肽QSAR建模[J].物理化学学报,2011,27(07):1654-1660.[SCI收录])

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