專家信息：

趙興明，男，同濟大學電子與信息工程學院教授，同濟大學智能感知網高等研究院研究員，博士生導師。 

教育及工作經歷：

2000年，吉林大學工學學士學位。

2003年，吉林大學工學碩士學位。

2005年，獲中國科技大學模式識別與智能系統專業博士學位。

2004年至2005年，在香港浸會大學計算機系作Research Assistant。

2006年至2008年，在東京大學作研究員。

2010年6月-2011年12月，在德國歐洲分子生物學實驗室(EMBL)做博士后研究。

現任同濟大學電子與信息工程學院教授，同濟大學智能感知網高等研究院研究員。

學術兼職及社會任職：

1. IEEE Senior Member委員。

2. IEEE SMC Technical Committee on Systems Biology委員。

3. IAPR TC20 (Technical Committee on Pattern Recognition for Bioinformatics) 委員會，委員。

4. 中國運籌學會計算系統生物學分會理事。

5. 中國細胞學會功能基因組信息學與系統生物學分會理事。

6. 上海市生物信息學協會理事。

6. Neurocomputing、Journal of Theoretical Biology和BioMed Research International等多個國際雜志的客座編輯和編委。

Editorships and Editorial Boards:

1. Lead Guest Editor, BioMed Research International (IF=2.9, 2013-)

2. Lead Guest Editor, IET Systems Biology (IF=1.3, 2013-)

3. Lead Guest Editor, The Scientific World Journal (IF=1.6, 2012-)

4. Guest Editor, Journal of Theoretical Biology (IF=2.4, 2013-)

5. Guest Editor, Current Bioinformatics (IF=1.6, 2012-)

6. Academic Editor, Journal of Scientific Research and Reports (2013-)

7. Editorial board member, Journal of Bioinformatics in Nutrition (2012-)

8. Editorial board member, Computational Biology Journal (2012-)

9. Editorial board member, The Open Access Journal of Science and Technology (OAJoST) (2012-) 

Service at Professional Society:

1. Senior Member, IEEE

2. Member, IEEE SMC Technical Committee on Systems Biology

3. Member, IAPR Technical Committee on Pattern Recognition for Bioinformatics

4. Member, CAAI Society of Bio-informatics and Artificial Life

5. Member, International Society for Computational Biology

6. Member, Shanghai Bioinformatics Society

7. Member, Chinese Computational Systems Biology Society

8. Member, Program Committee, InCoB2013 (12th International Conference on Bioinformatics of the Asia-Pacific Bioinformatics Network)

9. Member, Program Committee, ICTBI2012 (The International Conference on Translational Biomedical Informatics)

10. Member, Program Committee, International Conference on Intelligent Computing, 2009-2013

11. Member, Program Committee, IEEE BIBM Conference, 2010-2012

12. Program Chair, 8th IAPR International Conference on Pattern Recognition in Bioinformatics

13. Session Chair, Bio-Molecular Network session, 48th IEEE Conference on Decision and Control, 2009

14. Session Chair, Systems Biology session, The 2009 IEEE International Conference on ystems, Man, and Cybernetics, 2009

主講課程：

資料更新中…… 

培養研究生情況：

所指導學生已經分赴法國昂熱大學、日本東京大學、香港中文大學和華為等單位深造和工作，并先后獲得國家獎學金和國際會議最佳學術論文等多種榮譽。

招聘情況：

歡迎對機器學習、數據挖掘、復雜網絡、計算系統生物學和最優化感興趣的同學和同仁加入我們組。

研究方向：

1. 計算系統生物學：疾病基因的預測、藥物靶標的預測、藥物重定位和生物分子網絡的推斷等。

2. 圖論與最優化：線性規劃、圖著色、圖游走與標記傳播等。

3. 文本挖掘：生物醫藥文獻的深度挖掘與知識發現和語義網絡的構建等。

承擔科研項目情況：

主持完成國家863課題1項，上海市教委創新基金1項，上海市青年科技啟明星計劃1項，以及國家重點實驗室開放課題等多項課題。目前主持在研國家自然科學基金2項、上海市教委創新基金重點項目1項，中-法“蔡元培”合作交流項目1項，美國孟山都合作項目1項等多項課題。

Construction and analysis of molecular networks, including protein - protein interaction network and gene regulatory networks.

Recognition of disease associated molecular pathways and gene modules.

Drug - protein interaction, drug - drug interactions and the prediction of drug combination

科研成果：

1. 在PLoS Computational Biology、Bioinformatics、Current Opinion in Biotechnology、Neucleic Acids Research、Plant Physiology、Journal of Proteome Research、Neural Networks和Pattern Recognition等國際著名學術期刊發表學術論文60余篇，其中SCI檢索論文50余篇。參與編寫專著3部。

2. 在藥物重新定位的研究過程中，應當系統地綜合考慮疾病產生的分子機制及其所涉及和影響的分子網絡特征，以及藥物所影響的分子網絡特征，這將會大大提高藥物重新定位的準確率。在過去的3年里，趙興明和他的團隊針對“藥物重新定位”開展了深入的研究，最近他在乳腺癌藥物重定位方面取得了很大進展，他針對乳腺癌所識別的藥物，不僅在多個乳腺癌細胞細胞系上得到了驗證，而且可以很好地抑制小鼠體內的腫瘤生長。

resource： 

EFG 

2013,22,Jun 

eFG (ebook for Fusarium Graminearum) is an information query system for the pathogenic fungus Fusarium graminearum. It contains many information for F. graminearum that the sequences, proteins, annotations, protein-protein interaction, pathogenic genes, sub-location of proteins, transcription factors and ortholog information with other fungi. 

 
 

NARROMI 

2013,1,Jan 

NARROMI is software for improving accuracy of GRNs inference. It is a novel method combining ordinary differential equation based recursive optimization (RO) and information-theory based mutual information (MI). In this algorithm, both noisy regulations with low pair-wise correlations and redundant regulations from indirect regulators are removed by measuring MI and implementing RO, respectively. In particular, it is the first one to handle the redundancy problem in GRNs for model based network inference methods. 

 

PCA-CMI 

2011,17,Nov 

PCA-CMI is a MATLAB program for inferring gene regulatory networks from gene expression data. It is a novel method based on path consistency algorithm and conditional mutual information, which consider the non-linear dependence and topological structure of GRNs. In this algorithm, the (conditional) dependence between a pair of genes is represented by the CMI between them. With the general hypothesis of Gaussian distribution underlying gene expression data, CMI between a pair of genes is computed by a concise formula involving the covariance matrices of the related gene expression profiles. 

 

DIPOS 

2011,29,Jun 

DIPOS provides a complete rice protein interaction database to the plant biologist to better understand the life of plants, especially for rice.

 

FPPI 

2009,9,May 

FPPI is a database about protein-protein interactions for Fussarium graminearum, which contain 223,116 interactions among 7,406 proteins and 27,102 interactions among 3,745 proteins in the core PPI set. Furthermore, this database contains various different functional information for F. graminearum genes.
 

CMI2NI

--- 

CMI2NI is a software for inferring gene regulatory networks from gene expression data. It is a novel method using a new proposed concept of Conditional Mutual Inclusive Information (CMI2) which can accurately measure direct dependences between genes. Given the small size samples of gene expression data, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the dependence or regulation strength between genes. CMI2NI provides a useful tool to infer gene regulatory networks.

在PLoS Computational Biology、Bioinformatics、Current Opinion in Biotechnology、Neucleic Acids Research、Plant Physiology、Journal of Proteome Research、Neural Networks和Pattern Recognition等國際著名學術期刊發表學術論文60余篇，其中SCI檢索論文50余篇。參與編寫專著3部。

代表性英文論文：

2015

1. Wang YY, Li Z, Chen T, Zhao XM. 2015. Understanding the aristolochic acid toxicities in rat kidneys with regulatory networks. IET Syst Biol, 9(4):141-6. doi: 10.1049/iet-syb.2014.0057.

2. Zhao XM. 2015. Guest Editorial. IET Syst Biol, 9(4):105. doi: 10.1049/iet-syb.2015.0057.

3. Dai YF, Zhao XM. 2015. A survey on the computational approaches to identify drug targets in the postgenomic era. Biomed Res Int, 2015:239654. doi: 10.1155/2015/239654. Epub 2015 Apr 28. Review.

4. Downs CA, Kreiner L, Zhao XM, Trac P, Johnson NM, Hansen JM, Brown LA, Helms MN. 2015. Oxidized glutathione (GSSG) inhibits epithelial sodium channel activity in primary alveolar epithelial cells. Am J Physiol Lung Cell Mol Physiol, 308(9):L943-52. doi: 10.1152/ajplung.00213.2014. Epub 2015 Feb 20.

5. Zhang X, Zhao J, Hao JK, Zhao XM, Chen L. 2015. Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks. Nucleic Acids Res, 43(5):e31. doi: 10.1093/nar/gku1315. Epub 2014 Dec 24.

6. Zhao XM, Liu KQ, Zhu G, He F, Duval B, Richer JM, Huang DS, Jiang CJ, Hao JK, Chen L. 2015. Identifying cancer-related microRNAs based on gene expression data. Bioinformatics, doi: 10.1093/bioinformatics/btu811. Epub 2014 Dec 12.

7. Wang HQ, Zheng CH, Zhao XM. 2015. jNMFMA: a joint non-negative matrix factorization meta-analysis of transcriptomics data. Bioinformatics, 31(4):572-80. doi: 10.1093/bioinformatics/btu679. Epub 2014 Oct 16.

2014

8. Wang M#, Zhao XM#, Tan H, Akutsu T, Whisstock J, and Song J. 2014. Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets. Bioinformatics, 30(1): 71-80.

9. Chen WH, Zhao XM, Noort V and Bork P. 2014. Comments on "Human Dominant Disease Genes Are Enriched in Paralogs Originating from Whole Genome Duplication". PLoS Computational Biology, 10(7): e1003758.

10. Hong-Qiang Wang, Chun-Hou Zheng and Xing-Ming Zhao. 2014 jNMFMA: A joint non-negative matrix factorization meta-analysis of transcriptomics data. Bioinformatics, doi:10.1093/bioinformatics/btu679.

11. Xing-Ming Zhao, Luonan Chen 2014. Network-based biomarkers for complex diseases. Journal of Theoretical Biology. pii: S0022-5193(14)00400-7. doi: 10.1016/j.jtbi.2014.07.007.

12. Xing-Ming Zhao, Alioune Ngom, Jin-Kao Hao 2014. Pattern recognition in bioinformatics. Neurocomputing, 145:1-2.

13. Guimin Qin, Xing-Ming Zhao* 2014. A survey on computational approaches to identifying disease biomarkers based on molecular networks. Journal of theoretical biology, pii: S0022-5193(14)00344-0. doi: 10.1016/j.jtbi.2014.06.007.

14. Zhao XM, Gao JX, Nacher JC 2014. Data mining in translational bioinformatics. BioMed Research International. 2014: 656519.

15. Li S, Kang L, and Zhao XM* . 2014. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics. BioMed Research International 2014: 362738.

16. Zhao, XM. 2014. Editorial: Part 1: Network biology in translational bioinformatics and systems biology. IET Systems Biology 8(2): 23.

17. Zhao, XM. 2014. Editorial: Part 2: Network biology in translational bioinformatics and systems biology. IET Systems Biology 8(3): 75.

2013

18. H Wang , H Zheng, Azuaje, F, Xing-Ming Zhao. (2013). "Drug-Domain Interaction Networks in Myocardial Infarction". IEEE Transactions on, NanoBioscience, 12(3), 182-188.

19. Wei-Hua Chen, Xing-Ming Zhao, Vera van Noort and Peer Bork. "Human monogenic disease genes have frequently functionally redundant paralogs". PLoS Computational Biology, 2013, 9(5): e1003073. (Co-first author)

20. Xiaoping Liu, Xiao-Dong Zhang, Wei-Hua Tang, Luonan Chen and Xing-Ming Zhao*. "eFG: an electronic resource for Fusarium graminearum". Database, doi: 10.1093/database/bat042, 2013.

21. Xiaoping Liu, Rui Liu, Xing-Ming Zhao and Luonan Chen. Detecting early-warning signals of type 1 diabetes and its leading biomolecular networks by dynamical network biomarkers"[J]. BMC Medical Genomics, 2013, 6(2): 1-10.

22. Xing-Ming Zhao, Weidong Tian, Jiang R, Wan J. "Computational Systems Biology". The Scientific World Journal. 2013: 350358. (Editorial)

23. Xing-Ming Zhao. "Network Biology: Towards Systematic Understanding of Biological Systems". Current Bioinformatics. 2013, 8(1):35-36. (Editorial)

24. Chenglei Sun, Zheng-Zheng Shi, Xiaobo Zhou, Luonan Chen, Xing-Ming Zhao*."Prediction of S-Glutathionylation Sites Based on Protein Sequences". PLoS ONE, 2013, 8(2): e55512.

25. Xiujun Zhang, Keqin Liu, Zhi-Ping Liu, Béatrice Duval, Jean-Michel Richer, Xing-Ming Zhao*, Jin-Kao Hao and Luonan Chen. "NARROMI: a noise and redundancy reduction technique improves accuracy of gene regulatory network inference". Bioinformatics, 2013, 29(1):106-113.

26. Xiao-Dong Zhang, Xing-Ming Zhao*. "Computational approaches for identifying signaling pathways from molecular interaction networks", Current Bioinformatics, 2013, 8(1): 56-62.

2012

27. Jiao Wang, Fuyan Hu, Hua Cheng, Xing-Ming Zhao*, TieqiaoWen. "A systems biology approach to identifying the signaling network regulated by Rho-GDI-γ during neural stem cell differentiation", Molecular BioSystems, 2012, 8, 2856-2923.

28. Mingjun Wang, Xing-Ming Zhao, Haisong Xu, Yuan Li, Tatsuya Akutsu, Jiangning Song. "FunSAV: predicting the functional effect of single amino acid variants using a two-stage random forest model", PLoS ONE, 2012, 7(8):e43847.

29. Haiying Wang, Huiru Zheng, Francisco Azuaje, Xingming Zhao. "Drug-Target Network in Myocardial Infarction: a Structural Analysis", the 2012 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2012).

30. Ke-Qin Liu, Zhi-Ping Liu, Jin-Kao Hao, Luonan Chen, Xing-Ming Zhao*. "Identifying dysregulated pathways in cancers from pathway interaction networks", BMC Bioinformatics, 2012, 13: 126.

31. Xiaoping Liu, Zhi-Ping Liu, Xing-Ming Zhao*, Luonan Chen. "Identifying disease genes and module biomarkers by differential interactions", J Am Med Inform Assoc, 19: 241-248, 2012.

32. Yin-Ying Wang, Jose C.Nacher, Xing-Ming Zhao*. "Predicting drug targets based on protein domains", Mol Biosyst, 8(5):1528-1534, 2012.

33. Yin-Ying Wang, Ke-Jia Xu, Jiangning Song, Xing-Ming Zhao*. "Exploring drug combinations in genetic interaction network", BMC Bioinformatics, 13(Suppl 7): S7, 2012.

34. Xiujun Zhang, Xing-Ming Zhao, Kun He, Le Lu, Yongwei Cao, Jingdong Liu, Jin-Kao Hao, Zhi-Ping Liu, Luonan Chen. "Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information", Bioinformatics, 28(1):98-104, 2012. 

2011

35. Xing-Ming Zhao, Murat Iskar, Georg Zeller, Michael Kuhn, Vera van Noort, Peer Bork, "Prediction of drug combinations by integrating molecular and pharmacological data", PLoS Comput Biol, Dec; 7(12): e1002323, 2011.

36. Murat Iskar, Georg Zeller, Xing-Ming Zhao, Vera van Noort, Peer Bork, "Drug discovery in the age of systems biology: the rise of computational approaches for data integration", Curr Opin Biotechnol. Dec 5, 2011.

37. Achyut Sapkota, Xiaoping Liu, Xing-Ming Zhao*, Yongwei Cao, Jingdong Liu, Zhi-Ping Liu, Luonan Chen. "DIPOS: database of interacting proteins in Oryza sativa", Molecular BioSystems, 7(9):2615-2621, 2011. 

2010

38. Xiang Tang, Zhi-Yong Zhang, Wen-Juan Zhang, Xing-Ming Zhao, Xuan Li, Dong Zhang, Qiao-Quan Liu and Wei-Hua Tang, "Global Gene Profiling of Laser-Captured Pollen Mother Cells Indicates Molecular Pathways and Gene Subfamilies Involved in Rice Male Meiosis", Plant Physiology, 154:1855-1870, 2010.

39. Xiaoping Liu, Wei-Hua Tang, Xing-Ming Zhao*, Luonan Chen, "A network approach to predict pathogenic genes for Fusarium graminearum", PLoS ONE, 5(10): e13021, 2010.

40. Jun-Feng Xia, Xing-Ming Zhao, Jiangning Song, De-Shuang Huang, "APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility", BMC Bioinformatics, 11:174, 2010.

41. Jun-Feng Xia, Xing-Ming Zhao, De-Shuang Huang, "Predicting protein-protein interactions from protein sequences using meta predictor", Amino Acids, 39(5):1595-9, 2010.

42. Zikai Wu, Xing-Ming Zhao*, Luonan Chen, "A Systems biology approach to identify effective cocktail drugs", BMC Systems Biology (OSB2009 special issue), 4(Suppl 2): S7, 2010.

43. Chenglei Sun, Xing-Ming Zhao*, Weihua Tang, Luonan Chen, "FGsub: Fusarium graminearum protein subcellular localization prediction from primary structures", BMC Systems Biology (OSB2009 special issue), 4(Suppl 2): S12, 2010.

44. Xing-Ming Zhao, Yiu-Ming Cheung, De-Shuang Huang. "Analysis of Gene Expression Data Using RPEM Algorithm in Normal Mixture Model with Dynamic Adjustment of Learning Rate",International Journal of Pattern Recognition and Artificial Intelligence, 24(4): 651-666, 2010.

45. Xing-Ming Zhao, Luonan Chen, and Kazuyuki Aihara, "A discriminative approach to identifying domain-domain interactions from protein-protein interactions", Proteins, 78:1243-1253, 2010.

46. Xing-Ming Zhao, Yixue Li, Ming Li, Luonan Chen, "Advances in genome informatics", Journal of Bioinformatics and Computational Biology, 8 Suppl 1: v-viii, 2010. 

2009

47. Xing-Ming Zhao, Xiao-Wei Zhang, Weihua Tang, Luonan Chen, "FPPI: Fusarium graminearum protein-protein interaction database", Journal of Proteome Research, 8 (10): 4714-4721, 2009.

48. Zikai Wu, Xing-Ming Zhao, Luonan Chen, "Identifying responsive functional modules from protein-protein interaction network", Mol Cells, 27(3):271-277, 2009.

49. Xing-Ming Zhao, Ruisheng Wang, Luonan Chen, and Kazuyuki Aihara, "Automatic modeling of signaling pathways by network flow model", J Bioinform Comput Biol, 7(2):309-322, 2009. 

2008

50. Xing-Ming Zhao , Ruisheng Wang, Luonan Chen, and Kazuyuki Aihara, "Uncovering signal transduction networks from high-throughput data by integer linear programming", Nucl. Acids Res, 36(9):e48, 2008.

51. Xing-Ming Zhao , Yong Wang, Luonan Chen, Kazuyuki Aihara, "Gene function prediction using labeled and unlabeled data", BMC Bioinformatics, 9:57, 2008 .

52. Xing-Ming Zhao , Xin Li, Luonan Chen, Kazuyuki Aihara, "Protein classification with imbalanced data", Proteins, 70(4):1125-1132, 2008.

53. Xing-Ming Zhao , Yong Wang, Luonan Chen, Kazuyuki Aihara, "Protein domain annotation with integration of heterogeneous information sources", Proteins, 72(1):461-473, 2008.

54. Xing-Ming Zhao , Luonan Chen and Kazuyuki Aihara, "Protein function prediction with high-throughput data", Amino Acids, 35(3): 517-530, 2008. 

2006

55. Xing-Ming Zhao , Ji-Xiang Du, Hong-Qiang Wang, Yunping Zhu, and Yixue Li, "A new technique for selecting features from protein sequences", International Journal of Pattern Recognition and Artificial Intelligence, 20(2): 271–283, 2006.

56. De-Shuang Huang, Xing-Ming Zhao , Guang-Bin Huang,Yiu-Ming Cheung, "Classifying protein sequences using hydropathy blocks", Pattern Recognition, 39: 2293 – 2300, 2006. 

2005

57. Xing-Ming Zhao , Yiu-Ming Cheung, and De-shuang Huang, "A novel approach to extracting features from motif content and protein composition for protein sequence classification",Neural Networks, 18(8): 1019-1028, 2005.

58. Xing-Ming Zhao , Yiu-Ming Cheung, De-Shuang Huang, "A novel Markov pairwise protein sequence alignment method for sequence comparison", Protein and Peptide Letters, 12(7):665-669, 2005.

榮譽獎勵：

1、2010年，入選上海市青年科技啟明星。

2、2013年，入選上海市浦江人才計劃。

 

9月19日，應我院趙興明教授的邀請，英國Ulster大學Haiying Wang教授來到嘉定校區，在智信館403室作了題為“Dynamics and Controllability in Cell Cycle Specific Protein Interaction Networks”的學術報告，此報告也是計算機科學與技術系智信講壇第45期。 

報告會上，Haiying Wang教授首先系統地介紹了了蛋白質相互作用網絡動態組織規律的研究背景，接著介紹了以酵母細胞周期實驗數據驅動的動態過程研究，以及在細胞周期生物過程中兩類hub基因（data hub和party hub）起到的作用和各自特點，最后介紹了基于minimum dominating set方法所識別出的關鍵蛋白（critical protein）和多余蛋白（redundant protein）在蛋白質相互作用網絡中的拓撲結構特點、基因組中的必要性、功能相似性和在網絡中的恢復力。報告過程中，我院學生與Haiying Wang教授交流充分，氣氛熱烈。 

報告結束后，Haiying Wang教授與趙興明教授討論了具體的合作事宜。 

 

來源：同濟大學計算機科學與技術系 2015-10-08

同濟大學高等研究院趙興明研究員應邀來我室作學術報告

10月23日，同濟大學高等研究院研究員趙興明應邀來我室進行學術交流并作了題為“Computational approaches to reverse engineering gene regulatory networks”的學術報告。趙興明研究員為上海市青年科技啟明星計劃入選者、上海市浦江人才計劃入選者。擔任IEEE Senior Member、IEEE SMC Technical Committee on Systems Biology委員、IAPR TC20 委員、中國運籌學會計算系統生物學分會理事、中國細胞學會基因組信息學與系統生物學分會理事和上海市生物信息學學會理事。同時擔任了Journal of Theoretical Biology和BioMed Research International 等國際雜志的客座編輯和編委。已完成了863在內的多項科研課題，發表SCI檢索論文50余篇。

來源：中國科學院海洋環流與波動重點實驗室 2014-10-24 

醫學系統生物學學組在我校召開成立會議

為促進計算系統生物學與醫學的交叉融合，特別是在轉化醫學研究中的應用。5月11日—12日，中國運籌學會計算系統生物學分會在我校召開醫學系統生物學學組成立會議。

會議由醫學系統生物學學組組長沈百榮教授主持,陳洛南教授代表計算系統生物學分會對醫學系統生物學學組成立表示祝賀并做特邀報告。張世華 (中國科學院數學與系統科學研究院)；戴曉峰 (江南大學生物工程學院)；高琳(西安電子科技大學計算機學院)；劉雷 (復旦大學生物醫學研究院)；薛宇 (華中科技大學生命科學與技術學院)；王海蕓(同濟大學生命科學院)；王侃侃 (上海交通大學醫學院附屬瑞金醫院)；王勇 (中國科學院數學與系統科學研究院)；王進(南京大學生命科學院);吳凌云(中國科學院數學與系統科學研究院)；趙興明(同濟大學電子與信息工程學院)等12位專家結合自己的研究工作做了豐富精彩的專題報告，討論了大數據時代的系統生物學與其它學科交叉的迫切性和學組成立、發展的重要性。

學術會議結束后，評彈學校青年藝術家孫可老師介紹了蘇州評彈藝術并作了精彩表演，大家饒有興致的討論了科學與藝術結合對創新思維促進的系統生物學基礎。會議確定10月份在青島舉行醫學系統生物學學組第一次workshop。

來源：蘇州大學國家技術轉移中心 2014-05-15