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戴晓峰

教授

18168870169

0510-85329306

E-mail

Xiaofeng.dai@jiangnan.edu.cn

教育经历:

2011/02 – 2013/09,赫尔辛基大学中心医院,妇产科,博士后

2010/02 – 2011/04,芬兰分子医药研究中心,博士后

2011/08 – 2016/11,阿尔托大学,商学院,博士(计量经济学)

2007/03 – 2010/01,坦贝雷工业大学,计算与电子工程系,博士(计算系统生物学)

2007/08 – 2010/01,坦贝雷大学,硕士(生物信息)

2003/09 – 2006/07,中国农业科学院,硕士(生物化学与分子生物学)

1999/09 – 2003/07,中国林业科技大学,学士(生物技术)

学术兼职:

2017/08–今,中国系统生物学学会功能基因组学与系统生物学分会,理事

2015/05–今,生物信息学会,会员

研究方向:

围绕着乳腺癌精准医疗长期从事遗传学、生物信息学以及相关交叉学科研究,致力于将干、湿实验有机结合解决三阴性乳腺癌的靶向治疗问题。

主要在研项目:

科研项目名称

项目性质

总经费

时间

项目号

基底型乳腺癌干细胞信号传导网络结构建模

国家自然科学基金面上项目

80万元

2015-2018

31471251

三阴性乳腺癌的表观遗传学靶向治疗方法探索

江苏省自然科学基金面上项目

10万元

2016-2019

BK20161130

常压等离子体辅助DNA去甲基化治疗三阴性乳腺癌方法探索

江苏省六大人才高峰

4万元

2016-2019

SWYY-128

全悬浮培养细胞的驯化和新型悬浮细胞株的研发

北京大北农横向经费

100万元 【可追加】

2016-2020

研究生招生专业:

发酵工程

代表性学术成果(论文、专利等):

X.F. Dai#*, X. Chen, Q.W. Fang, J. Li, Z.H. Bai*, “Inducible CRISPR genome-editing tool: classifications and future trends”, Critical Reviews in Biotechnology, 2017, inpress.

X.F. Dai#*, T.Y. Hua, T.T. Hong, “Integrated diagnostic network construction reveals a 4-gene panel and 5 cancer hallmarks driving breast cancer heterogeneity”, Scientific Reports, 2017, 10.1038/s41598-017-07189-6.

X.F. Dai#*, Y.H. Cheng, Z.H. Bai, J. Li, “Breast cancer cell line classification and its relevance with breast tumor subtyping”, Journal of Cancer, 2017, in press.

X.F. Dai#*, A. Chen, Z. Bai, “Integrative investigation on breast cancer in ER, PR and HER2-defined subgroups using mRNA and miRNA expression profiling”, Scientific Reports, 2014, 4(6566).

X.F. Dai#, R. Fagerholm, S. Rafiq, C. Blomgvist, H. Nevanlinna*, “INPP4B and RAD50 have an interactive effect on survival after breast cancer”, Breast Cancer Research and Treatment, 2015, 149(2), 363-371.

X.F. Dai#, L. Li, X. Liu, W. Hu, Y. Yang*, Z. Bai*, “Cooperation of DLC1 and CDK6 affects breast cancer clinical outcome”, G3: Genes, Genomes, Genetics, 2015, 5(1), 81-91.

X.F. Dai#, T. Kuosmanen*, “Best-practice benchmarking using clustering methods: Application to energy regulation”, Omega, 2014, 42(1), 179-188.

X.F. Dai#*, “Non-parametric efficiency estimation using Richardson-Lucy blind deconvolution”, European Journal of Operational Research, 2016, 248(2), 731-739.

X.F. Dai#, Z.Q. Liu, S. Zhang*, “Over-expression of EPS15 is a favorable prognostic factor in breast cancer”, Molecular BioSystems, 2015, 11(11), 2978 - 2985.

X.F. Dai#*, W. Guo, C. Zhan, X. Liu, Z. Bai, Y. Yang*, “WDR5 over-expression is prognostic of poor breast cancer outcome”, PLOS ONE, 2015, 10(9), e0124964. DOI: 10.1371/journal.pone.0124964.

X.F. Dai#*, T. Li, Z. Bai, Y.K. Yang, X.X. Liu, J.L. Zhan, B. Shi, “Breast cancer intrinsic subtype classification, clinical use and future trends”, American Journal of Cancer Research, 2015, 10 (5).

X.F. Dai#, Y. Li, Z. Bai, X. Tang*, “Molecular portraits revealing the heterogeneity of breast tumor subtypes defined using immunohistochemistry”, Scientific Reports, 2015, 5(14499), doi: 10.1038/srep14499.

X.F. Dai#*, L.J. Xiang, T. Li, Z. Bai, “Cancer hallmarks, biomarkers and breast cancer molecular subtypes”, Journal of Cancer, 2016, 7(10), 1281-1294.

X.X. Liu#, W.G. Hu#, Z.F. An, Z.H. Bai,X.F. Dai*, Y.K. Yang*, Exploration of cell lysis in a bioreactor using Escherichia coli expressing single-chain variable-domain antibody fragments, Annals of Microbiology, 2016, 1-9.

X.F. Dai#, O. Yli-Harja, and A.S. Ribeiro*, “Determining noisy attractors of delayed stochastic Gene Regulatory Networks from multiple data sources”, Bioinformatics, 2009, 25(18), 2362-2368.

A.S. Ribeiro#*,X.F. Dai, Olli Yli-Harja, “Variability of the distribution of differentiation pathway choices regulated by a multipotent delayed stochastic switch”, Journal of Theoretical Biology, 2009, 260(1), 66-76.

X.F. Dai#, Shannon Healy, O. Yli-Harja, and A.S. Ribeiro*, “Tuning cell differentiation patterns and single cell dynamics by regulating proteins functionalities in a Toggle Switch”, Journal of Theoretical Biology, 2009, 261(3), 441-448.

X.F. Dai#, T. Erkkilä, O. Yli-Harja and H. Lähdesmäki*, “A joint mixture model for clustering genes from Gaussian and beta distributed data”, BMC Bioinformatics, 2009, 10, 165.

X.F. Dai#, O. Yli-Harja, and H. Lähdesmäki*, “Novel Data Fusion Method and Exploration of Multiple Information Sources for Transcription Factor Target Gene Prediction”, EURASIP Journal on Advances in Signal Processing, 2010, 2010(235795), doi:10.1155/2010/235795.

X.F. Dai#, H. Lähdesmäki, and O. Yli-Harja*, “A stratified beta-Gaussian mixture model for clustering genes with multiple data sources”, International Journal On Advances in Life Sciences, 2009, 1(1), 14-25.

X.F. Dai#*, “NMM-StoNED: a normal mixture model based stochastic semi-parametric benchmarking method”, International Journal of Business and Management Study, 2015, 2(2).

获奖及荣誉:

2016 六大人才高峰计划

2015 无锡市社会事业领军人才

2010 国家海外优秀自费留学生奖学金

资料更新日期:2017/08/24