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研究人員 ｜ Research Faculty

● Associate Research Fellow, Institute of Information Science, ƒ The Ten Outstanding Young Women Award, 1998
宋定懿 Ting-Yi Sung Academia Sinica (1989-2000) (第十七屆十大傑出女青年 )
● MBA, State University of New York at Buffalo (1983)
● B.S., Management Science, National Chiao Tung University (1980)
研究員 Research Fellow
Ph.D., Operations Research, New York University
Tel: +886-2-2788-3799 ext. 1711
Fax: +886-2-2782-4814
Email: tsung@iis.sinica.edu.tw
http://www.iis.sinica.edu.tw/pp./tsung/eindex.html

代表著作 Publications

1. Chien-Ping Chang, Ting-Yi Sung and Lih-Hsing Hsu, Edge conges- 8:325, 2007.
tion and topological properties of crossed cubes, IEEE Transactions 15. Chuan-Yih Yu, Yin-Hao Tsui, Yi-Hwa Yian, Ting-Yi Sung and Wen-
研究簡介 Research Description on Parallel and Distributed Systems, vol. 11, pp. 64--80, 2000. Lian Hsu, The Multi-Q web server for multiplexed protein quantita-
2. Jeng-Jung Wang, Chun-Nan Hung, Jimmy J.M. Tan, Lih-Hsing Hsu tion, Nucleic Acids Research, vol. 35 (Web Server issue), No. suppl_2,
我的研究領域為蛋白體學上的生物資訊，包括：以質譜 My current research interest is in bioinformatics with focus on proteomics, including and Ting-Yi Sung, Construction schemes for fault tolerant Hamilto- W707-W712, 2007.
儀資料為基礎的蛋白體分析以及蛋白質不同預測問題。 mass spectrometry-based proteomics and protein prediction problems. nian graphs, Networks, vol. 35, pp. 233--245, 2000. 16. Emily Chia-Yu Su, Hua-Sheng Chiu, Allan Lo, Jenn-Kang Hwang,
3. Tseng-Kuei Li, Jimmy J.M. Tan, Ting-Yi Sung and Lih-Hsing Hsu, Ting-Yi Sung and Wen-Lian Hsu, Protein subcellular localization
以質譜儀資料為基礎的蛋白體分析，主要包含蛋白質鑑 Mass spectrometry-based proteomics Optimum congested routing strategy on twisted cubes, Journal of In- prediction based on compartment-specific features and structure con-
定及蛋白質定量，以找出在不同細胞狀態(如：腫瘤細 Mass spectrometry (MS) has become a predominant method to comprehensively terconnection Networks, vol. 1, pp. 115--134, 2000. servation, BMC Bioinformatics, 8:330, 2007. Labeled “Highly ac-
胞與正常細胞)下表現量不同的蛋白質，以為開發新藥 characterize complex protein mixtures and post-translational modifications. MS- 4. Tseng-Kuei Li, Jimmy J.M. Tan, Lih-Hsing Hsu and Ting-Yi Sung, cessed”.
的可能標的。我們已經完成三套蛋白質定量自動化分析 based proteomic analysis involves protein identification and protein quantitation The shuffle-cubes and their generalization, Information Processing 17. Allan Lo, Hua-Sheng Chiu, Ting-Yi Sung, Ping-Chiang Lyu, Wen-
系統，分別為：用於 iTRAQ 標記定量的 Multi-Q 系統、 so that differentially expressed proteins between different cell states, e.g., tumor Letters, vol. 77, pp. 35--41, 2001 Lian Hsu, Enhanced membrane protein topology prediction using a
用於 ICAT 及 SILAC 標記定量的 MaXIC-Q 系統、以及用 cells and normal cells, can be identified to facilitate biomarker discovery. We have 5. Chun-Nan Hung, Lih-Hsing Hsu and Ting-Yi Sung, On the construc- hierarchical classification method and a new scoring function, Journal
of Proteome Research, vol. 7, pp. 487–496, 2008.
於無標記定量的 IDEAL-Q 系統；這三套系統涵蓋了目前 previously developed automated quantitation tools, including MaXIC-Q for stable tion of combined k-fault-tolerant hamiltonian graphs, Networks, vol.
常用的定量標記技術。這些系統是以蛋白質鑑定系統所 isotope labeling using MS/MS data (e.g., iTRAQ-lableing), MaXIC-Q for stable isotope 37, pp. 165--170, 2001. 18. Jia-Ming Chang, Emily Chia-Yu Su, Allan Lo, Hua-Sheng Chiu,
Ting-Yi Sung, and Wen-Lian Hsu, PSLDoc: protein subcellular locali-
產生的鑑定結果及質譜資料為輸入，進行分析。然而 labeling using MS data (e.g., ICAT- and SILAC-labeling), and IDEAL-Q for label-free 6. Jeng-Jung Wang, Ting-Yi Sung and Lih-Hsing Hsu, A family of opti- zation prediction based on gapped-dipeptides and probabilistic latent
在蛋白質鑑定上，目前常用的鑑定系統(如：Mascot 及 approach, that comprehensively cover major quantitation techniques. These tools mal 1-Hamiltonian graphs with diameter O(log n), Journal of Infor- semantic analysis, PROTEINS: Structure, Function, and Bioinformat-
mation Science and Engineering, vol. 17, no. 4, pp. 535--548, 2001.
SEQUEST)仍有以下困境；首先，他們往往產生不同的 are based on identification results from major search engines, e.g., Mascot and SE- ics, vol. 72, pp. 693-710, 2008.
鑑定結果。其次，他們對僅能鑑定少數種類的後轉譯修 QUEST. However, the protein identification results generated by these search tools 7. Kuen-Pin Wu, Hsin-Nan Lin, Jia-Ming Chang, Ting-Yi Sung and 19. Cheng-Wei Cheng, Emily Chia-Yu Su, Jenn-Kang Hwang, Ting-Yi
Wen-Lian Hsu, HYPROSP: A hybrid protein secondary structure pre-
飾蛋白質，如：磷酸化蛋白，但他們不見得能準確鑑定 are usually inconsistent and remain a problem for proteomic profiling. In case of diction algorithm- a knowledge-based approach, Nucleic Acids Re- Sung, and Wen-Lian Hsu, Predicting RNA-binding sites of proteins
修飾位置；再者，他們法鑑定許多重要的修飾蛋白質， post-translational modifications (PTMs), the identification problem becomes sub- search, vol. 32, pp. 5059-5065, 2004. using support vector machines and evolutionary information, BMC
如：醣蛋白。因此，我們將針對蛋白質鑑定進行研究， stantially harder since not only the sequence but also modification sites of a modi- 8. Hsin-Nan Lin, Jia-Ming Chang, Kuen-Pin Wu, Ting-Yi Sung and Bioinformatics, vol. 9 (Suppl 12), S6, 2008.
尤其是後轉譯修飾的蛋白質，如：磷酸化蛋白質的修飾 fied protein need to be determined. The existing search tools can only identify a few Wen-Lian Hsu, A knowledge-based hybrid method for protein sec- 20. Chih-Chiang Tsou, Yin-Hao Tsui, Yi-Hwa Yian, Yi-Ju Chen, Han-Yin
位置、醣蛋白的鑑定。 ondary structure prediction based on local prediction confidence, Bio- Yang, Chuan-Yih Yu, Ke-Shiuan Lynn, Yu-Ju Chen, Ting-Yi Sung,
types of PTMs and may not correctly identify their modification sites. Thus we start informatics, vol. 21, pp. 3227-3233, 2005. and Wen-Lian Hsu, MaXIC-Q Web: a fully automated web service
在蛋白質預測方面，我們以機器學習及知識庫的方法， to work on protein and peptide identification. In this area, we shall study identifica- 9. Tzong-Han Tsai, Shih-Hung Wu, Wen-Chi Chou, Yu-Chun Lin, Ding using statistical and computational methods for protein quantitation
based on stable isotope labeling and LC-MS, Nucleic Acids Research,
針對蛋白質結構、功能及交互作用進行預測。我們將針 tion of proteins with PTMs, e.g., phosphorylation and glycosylation. He, Ting-Yi Sung, Wen-Lian Hsu, Various criteria in the evaluation vol. 37 (Web Server issue), No. suppl_2, W661-W669, 2009.
對穿膜蛋白質進行結構預測，因為目前約有超過半數的 Protein prediction problems of biomedical named entity recognition, BMC Bioinformatics, 7:92,
藥物是這類蛋白質，用實驗方法鑑定他們的結構是非常 2006. 21. Allan Lo, Yi-Yuan Chiu, Einar Andreas Rødland, Ping-Chiang Lyu,
Ting-Yi Sung, and Wen-Lian Hsu, Predicting helix-helix interactions
費時且難解。此外，我們已發展出一套多重細胞位置預 The knowledge of protein structures and functions is crucial to the understanding 10. Ching-Tai Chen, Hsin-Nan Lin, Ting-Ying Sung and Wen-Lian Hsu, from residue contacts in membrane proteins, Bioinformatics, vol.
測的軟體工具，後續將針對不同物種及胞器之定位預測 of biological process. Since the experimental procedures for protein structure and A knowledge-based approach to protein local structure prediction, 25(8), pp. 996-1003, 2009.
進行研究。 function annotation are inherently low throughput, accurate computational tech- Journal of Bioinformatics and Computational Biology, vol. 4, pp. 22. Hsin-Nan Lin, Ching-Tai Chen, Ting-Yi Sung, Shinn-Ying Ho and
niques for protein structure and function prediction are indispensable. We will use 1287-1307, 2006. Wen-Lian Hsu, Protein subcellular localization prediction of eukaryo-
the machine learning approach and the knowledge based approach to predict pro- 11. Kuen-Pin Wu, Jia-Ming Chang, Jun-Bo Chen, Chi-Fon Chang, Wen- tes using a knowledge-based approach, BMC Bioinformatics, vol. 10
tein structures and functions. Particularly, we will study the structure prediction for Jin Wu, Tai-Huang Huang, Ting-Yi Sung and Wen-Lian Hsu, RIBRA- (Suppl 15), S8, 2009.
an error-tolerant algorithm for the NMR backbone assignment prob-
transmembrane proteins since they are prime drug targets. Moreover, we will also lem, Journal of Computational Biology,13(2), pp. 229-244, 2006. 23. Chih-Chiang Tsou, Chia-Feng Tsai, Ying-Hao Tsui, Putty-Reddy
work on protein subcellular localization prediction on different species. Sudhir, Yi-Ting Wang, Yu-Ju Chen, Jeou-Yuan Chen, Ting-Yi Sung,
12. Wen-Ting Lin, Wei-Neng Hung, Yi-Hwa Yian, Kun-Pin Wu, Chia-Li Wen-Lian Hsu, IDEAL-Q: An automated tool for label-free quantita-
Han, Yet-Ran Chen, Yu-Ju Chen, Ting-Yi Sung and Wen-Lian Hsu, tion analysis using an efficient peptide alignment approach and spec-
Multi-Q: A fully automated tool for multiplexed protein quantitation, tral data validation, Molecular and Cellular Proteomics, vol. 9, pp.
Journal of Proteome Research, vol. 5, pp. 2328-2338, 2006. 131-144, 2010.
13. Tzong-han Tsai, Wen-Chi Chou, Shih-Hung Wu, Ting-Yi Sung, Jieh
Hsiang, Wen-Lian Hsu, Integrating linguistic knowledge into a condi-
tional random field framework to identify biomedical named entities,
Expert Systems with Applications, 30 (1), pp. 117-128, 2006.
14. Richard Tzong-Han Tsai, Wen-Chi Chou, Ying-Shan Su, Yu-Chun
Lin, Cheng-Lung Sung, Hong-Jie Dai, Irene Tzu-Hsuan Yeh, Wei Ku,
Ting-Yi Sung and Wen-Lian Hsu, BIOSMILE: A semantic role labe-
ling system for biomedical verbs using a maximum-entropy model
with automatically generated template features, BMC Bioinformatics,
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