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代琦

发表于:2016-06-30  浏览人数:

别:男

出生年月:197909

称:副教授

组: 生物信息学

室: 0571-86843746

电子邮件:daiailiu04@yahoo.com

个人主页:http://bioinfo.zstu.edu.cn/daiqi

主要学习工作经历

1. 2000.09-2004.07 河南师范大学 本科学习

2. 2004.09-2009.05 大连理工大学 博士学习

3. 2009.05-2011.02 杭州电子科技大学 教师

4. 2011.02- 浙江理工大学 教师

主要学术及社会兼职

1. Journal of Computational Biology and Bioinformatics Research 编委

2. American Journal of Bioinformatics and Computational Biology编委

3. 浙江省生物信息学学会理事

4. 浙江省信号处理学会会员

主要研究方向

1. 功能基因组序列分析

2. 肿瘤蛋白质研究

3. 宫颈癌HPV分型研究

4. 乳腺癌早期诊断研究

获奖与荣誉

1. 荣获2006届博士生专项奖学金---“纪念向坊隆村井隆奖学金

2. 浙江省“151”人才第三层次

3. 浙江省高校中青年学科带头人

4. 浙江理工大学“521”拔尖人才

科研教学项目

1. “与肿瘤蛋白质结构、功能有关的信息处理问题研究国家自然科学基金,基金号:611703162012.1- 2015.12, 52万(负责人)

2. 面向宫颈癌HPV分型模型的生物序列比较及分类方法研究国家自然科学基金,基金号:610012142011.1- 2013.12, 24万(负责人)

3. “融合临床突变与序列的多重信息研究乳腺癌BRCA1/2基因突变区域浙江省自然科学基金,基金号:Y21009302011.1- 2013.12, 10万(负责人)

4. “卵巢癌化疗反应基因标志物辨识研究浙江省自然科学基金,基金号:Z20902992010.1- 2012.12, 35万(主要成员,3/7

5. “与生物序列结构、功能有关的数学方法研究,国家自然科学基金,基金号:108712192009.1- 2011.12, 23万(参与成员,6/9

6. “数学方法在计算分子生物学中的应用,国家自然科学基金,基金号:105710192006.1- 2008.12, 24万(参与成员,8/9

专著论文

1. Qi Dai*, Yan Li, Xiaoqing Liu, Yuhua Yao, Yunjie Cao, Pingan He. Comparison study on statistical features of predicted secondary structures for protein structural class prediction: From content to position. BMC Bioinformatics, 2013, 14: 152.

2. Qi Dai*, Xiaoqing Liu, Yuhua Yao, Fukun Zhao. Using Markov model to improve word normalization algorithm for biological sequence comparison. Amino Acids, 2012, DOI 10.1007/s00726-011-0906-2.

3. Qi Dai*, Xiaodong Guo, Lihua Li. Sequence comparison via polar coordinates representation and curve tree. Journal of Theoretical Biology, 2012, 292: 78-85.

4. Qi Dai*, Lihua Li, Xiaoqing Liu, Yuhua Yao, Fukun Zhao, Michael Zhang. Integrating Overlapping Structures and Background Information of Words Significantly Improves Biological Sequence Comparison. PLOS one, 2011. 6(11): e26779.

5. Qi Dai*, Wu Li, Lihua Li. Improving protein structural class prediction using novel combined sequence information and predicted secondary structural features. Journal of Computational Chemistry, 2011, 32: 3393-3398.

6. Qi Dai*, Xiaoqing Liu, Yuhua Yao, Fukun Zhao. Numerical characteristics of word frequencies and their application to dissimilarity measure for sequence comparison. Journal of Theoretical Biology, 2011, 276(1): 174-180.

7. Xiaoqing Liu, Qi Dai*, Lihua Li, Zerong He. An efficient binomial model-based measure for sequence comparison and its application. J Biomol Struct Dyn, 2011, 28(5):833-843.

8. Xiaoqing Liu, Qi Dai*, Lihua Li, Zhilong Xiu. Resistant mechanism against nelfinavir of subtype C human immunodeficiency virus type 1 proteases. Journal of Molecular Structure, 2011, 986: 30-38.

9. Qi Dai*, Xiaoqing Liu, Lihua Li, Yuhua Yao, Bin Han, Lei Zhu. Using Gaussian Model to Improve Biological Sequence Comparison. Journal of Computational Chemistry, 2010, 31: 351-361.

10. Shuyan Ding, Qi Dai, Hongmei Liu, Tianming Wang. A simple feature representation vector for phylogenetic analysis of DNA sequences, Journal of Theoretical Biology, 2010, 265(4):618-623.

11. Yuhua Yao*, Qi Dai, Ling Li, Xu-Ying Nan, Ping-An He, Yao-Zhou Zhang. Similarity/dissimilarity studies of protein sequences based on a new 2D graphical representation. Journal of Computational Chemistry, 2010, 31(5): 1045-1052.

12. Qi Dai*, Yanchun Yang, Tianming Wang. Markov model plus k-word distributions: A synergy that produces novel statistical measures for sequence comparison, Bioinformatics, 2008, doi: 10.1093/bioinformatics/btn436.

13. Qi Dai*, Tianming Wang. Comparison study on k-word statistical measures for protein: from sequence to 'sequence space'. BMC Bioinformatics, 2008, revised.

14. Qi Dai*, Tianming Wang. Use of linear regression model to compare RNA secondary structures, Journal of Theoretical Biology, 2008, 253(4):854-60

15. Qi Dai*, Tianming Wang. Use of statistical measures for analyzing RNA secondary structures, Journal of Computational Chemistry, 2008, 29: 1292-1305.

16. Yuhua Yao, Qi Dai, Xu-Ying Nan, Ping-An He, Zuo-Ming Nie, Song-Ping Zhou, Yao-Zhou Zhang. Analysis of similarity/dissimilarity of DNA sequences based on a class of 2D graphical representation , Journal of Computational Chemistry, 2008, 29: 1632-1639.

17. Yuhua Yao, Qi Dai, Chun Li, Ping-An He, Xu-Ying Nan, Yao-Zhou Zhang. Analysis of similarity/dissimilarity of DNA sequences based on a class of 2D graphical representation , Proteins: Structure, Function, and Bioinformatics, 2008, 10.1002/prot.22110.

18. Qi Dai*, Xiaoqing Liu, Tianming Wang. C(i,j) matrix: A better numerical characterization for graphical representations of biological sequences, Journal of Theoretical Biology, 2007, 247: 103-109.

19. Qi Dai*, Xiaoqing Liu, Tianming Wang, Vukicevic, Damir. Linear regression model of DNA sequences and its application, Journal of Computational Chemistry, 2007, 28: 1434-1445.

20. Qi Dai*, Xiaoqing Liu, Tianming Wang. Analysis of protein sequences and their secondary structures based on transition matrices. Journal of Molecular Structure-THEOCHEM, 2007, 803: 115-122.

21. Qi Dai*, Xiaoqing Liu, Tianming Wang. Numerical characterization of DNA sequences based on the k-step Markov chain transition probability . Journal of Computational Chemistry, 2006, 27: 1830-1842.

22. Qi Dai*, Xiaoqing Liu, Tianming Wang. A novel 2D graphical representation of DNA sequences and its application. Journal of Molecular Graphics & Modelling, 2006, 25: 340-344.

23. Xiaoqing Liu, Qi Dai, Zhilong Xiu, Tianming Wang, PNN-curve: A new 2D graphical representation of DNA sequences and its application. Journal of Theoretical Biology, 2006, 243: 555-561.

软件

1. PSCP-PSSE. An integrated computational software which implements sixteen statistical features of predicted secondary structures from content to position for protein structural class prediction ( http://bioinfo.zstu.edu.cn/PSCP-PSSE).

2. Mplusd. An integrated computational software which implements four statistical similarity measures proposed by us to measure the (dis)similarity of biological sequences.

3. SMPS-SS. An integrated computational software which implements six statistical measures for protein comparison, where the statistical measures are based on protein sequence or protein 'sequence space'.