童俊維

童俊維  研究員
生技與藥物研究所
Email: cwtung@nhri.edu.tw

 


學歷

  • 國立交通大學生物資訊研究所 博士 (2010)
  • 國立成​功大學生物學系 學士 (2005)

經歷

  • 國家衛生研究院生技與藥物研究所 研究員 (2021/08 – present)
  • 臺北醫學大學管理學院 副院長 (2020/08 – 2021/07​)
  • 臺北醫學大學國際生技醫療管理博士學位學程 主任 (2020/08 – 2021/07​)
  • 臺北醫學大學大數據科技及管理研究所 教授 (2020/02 – 2021/07)
  • 臺北醫學大學大數據科技及管理研究所 副教授 (2019/03 – 2020/01)
  • 高雄醫學大學藥學系 副教授 (2016/03 – 2019/02)
  • 國家衛生研究院國家環境醫學研究所 兼任助研究員 (2014/10 – 2021/07​)
  • 國家衛生研究院國家環境毒物研究中心 兼任助研究員 (2013/10 – 2014/09)
  • 美國國家毒理學研究中心 訪問學者 (2012/03 – 2012/05)
  • 高雄醫學大學藥學系 助理教授 (2011/08 – 2016/02)
  • 陸軍官校電機系 助教 (2011/02 – 2011/07)
  • 德國杜賓根大學計算機科學研究所 訪問學者 (2008/09 – 2009/08)​

研究興趣

化學資訊、生物資訊、計算毒理、藥物開發、機器學習、資料庫設計

研究成果

童俊維教授實驗室專注於開發人工智慧與資料庫技術應用於生物與化學分子的功能與毒性預測,目前已開發有ChemDIS與SkinSensDB、SkinSensPred等系統。目前已發表超過50篇科學著作,並受邀擔任包括Scientific Reports與Current Computer-Aided Drug Design等六個期刊的編輯委員會成員。

學術獲獎

  • 2021 – Excellent Research Paper Award (by Taipei Medical Univeristy, Taipei, Taiwan)
  • 2018 – Publons Peer Review Awards 2018 (Top 1% in Multidisciplinary)
  • 2017 – Best Presentation Award (by 2nd International Conference on Biomedical Signal and Bioinformatics, Auckland, New Zealand. Nov 27-30)
  • 2015 – Outstanding Research Award (by Kaohsiung Medical University, Kaohsiung, Taiwan)
  • 2014 – Outstanding Research Award (by Kaohsiung Medical University, Kaohsiung, Taiwan)
  • 2012 – Poster award (3rd place), International Conference on Bioinformatics and Computational Biology (BIOCOMP BG 2012), Varna, Bulgaria.
  • 2010 – The Research Excellence Award (by College of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan)
  • 2008 – The Scholarship of Sandwich Program for research visits to Germany (supported by DAAD of Germany and NSC of Taiwan)
  • 2008 – The Research Excellence Award (by College of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan)
  • 2007 – The Research Excellence Award (by College of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan)
  • 2004 – SUN Certified JAVA Programmer (SCJP 1.4)

近10年代表性論文(2011-2021)

  1. C.H. Hsu, H. Tomiyasu, J.J. Lee, C.W. Tung, C.H. Liao, C.H. Chuang, L.Y. Huang, K.W. Liao, C.H. Chou, A. T. C. Liao and C.S. Lin* (2021) Genome-wide DNA methylation analysis using MethylCap-seq in canine high-grade B-cell lymphomaJournal of Leukocyte Biology, 109(6), 1089-1103.
  2. H.L. Kan, C.C. Wang, Y.C. Lin* and C.W. Tung* (2021) Computational Identification of Preservatives with Potential Neuronal CytotoxicityRegulatory Toxicology and Pharmacology, 119, 104815.
  3. C.C. Yen, C.W. Tung, C.W. Chang, C.C. Tsai, M.C. Hsu* and Y.T. Wu* (2020) Potential Risk of Higenamine Misuse in Sports: Evaluation of Lotus Plumule Extract Products and a Human StudyNutrients, 12(2), 285.
  4. C.C. Wang, P. Lin, C.Y. Chou, S.S. Wang and C.W. Tung* (2020) Prediction of human fetal–maternal blood concentration ratio of chemicals, PeerJ, 8, e9562.
  5. C.W. Tung*, H.J. Cheng, C.C. Wang, S.S. Wang and P. Lin* (2020) Leveraging Complementary Computational Models for Prioritizing Chemicals of Developmental and Reproductive Toxicity Concern: An Example of Food Contact MaterialsArchives of Toxicology, 94, 485–494.
  6. P.I. Liang, C.C. Wang, H.J. Cheng, S.S. Wang, Y.C. Lin, P. Lin* and C.W. Tung* (2020) Curation of cancer hallmark-based genes and pathways for in silico characterization of chemical carcinogenesisDatabase (Oxford), 2020, baaa045.
  7. S.H. Huang, Y.C. Lin and C.W. Tung* (2020) Identification of time-invariant biomarkers for nongenotoxic hepatocarcinogen assessmentInternational Journal of Environmental Research and Public Health, 17(12), 4298.
  8. C.W. Tung*, Y.H. Lin and S.S. Wang (2019) Transfer Learning for Predicting Human Skin SensitizersArchives of Toxicology, 93(4), 931-940.
  9. C.W. Tung* and S.S. Wang (2018) ChemDIS 2: an update of chemical-disease inference systemDatabase (Oxford), 2018, bay077.
  10. C.W. Tung*, C.C. Wang, S.S. Wang and P. Lin* (2018) ChemDIS-Mixture: an online tool for analyzing potential interaction effects of chemical mixturesScientific Reports, 8, 10047.
  11. C.W. Tung*, C.C. Wang and S.S. Wang (2018) Mechanism-informed Read-across Assessment of Skin Sensitizers Based on SkinSensDBRegulatory Toxicology and Pharmacology, 94, 276-282.
  12. C.H. Tseng*, C.W. Tung, S.I. Peng, Y.L. Chen, C.C. Tzeng and C.M. Cheng* (2018) Discovery of Pyrazolo[4,3-c]quinolines Derivatives as Potential Anti-Inflammatory Agents through Inhibiting of NO ProductionMolecules, 23(5), 1036.
  13. Y.P. Liu, C.H. Chen, C.H. Yen, C.W. Tung, C.J. Chen, Y.M. A. Chen and M.S. Huang* (2018) Human immunodeficiency virus Tat-TIP30 interaction promotes metastasis by enhancing the nuclear translocation of Snail in lung cancer cell linesCancer Science, 109(10), 3105-3114.
  14. Y.L. Lin*, W.E. Huang, P.I. Liang and C.W. Tung (2018) An Integrated Web-based System for MEDLINE Analysis: A Case Study of Chronic Kidney DiseaseProceedings of 22nd Pacific Asia Conference on Information Systems (PACIS 2018), 1828-1840.
  15. C.C. Wang, Y.C. Lin, Y.C. Lin, S.R. Jhang and C.W. Tung* (2017) Identification of informative features for predicting proinflammatory potentials of engine exhaustsBiomedical Engineering Online, 16(Suppl 1), 66.
  16. C.C. Wang, Y.C. Lin, Y.H. Cheng and C.W. Tung* (2017) Profiling transcriptomes of human SH-SY5Y neuroblastoma cells exposed to maleic acidPeerJ, 5, e3175.
  17. C.C. Wang, Y.C. Lin, S.S. Wang, C. Shih, Y.H. Lin and C.W. Tung* (2017) SkinSensDB: a curated database for skin sensitization assaysJournal of Cheminformatics, 9, 5.
  18. C.H. Tseng, C.W. Tung, C.H. Wu, C.C. Tzeng, Y.H. Chen*, T.L. Hwang* and Y.L. Chen* (2017) Discovery of Indeno[1,2-c]quinoline Derivatives as Potent Dual Antituberculosis and Anti-Inflammatory AgentsMolecules, 22(6), 1001.
  19. S.H. Huang and C.W. Tung* (2017) Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogensScientific Reports, 7, 41176.
  20. C.W. Chang, C.W. Tung, C.C. Tsai, Y.T. Wu* and M.C. Hsu* (2017) Determination of cannabinoids in hemp nuts products in Taiwan by HPLC-MS/MS coupled with chemometric analysis: Quality evaluation and a pilot human studyDrug Testing and Analysis, 9(6), 888-897.
  21. C.C. Wang, Y.C. Lin, Y.C. Lin, S.R. Jhang and C.W. Tung* (2016) Prediction of Proinflammatory Potentials of Engine Exhausts by Integrating Chemical and Biological FeaturesChapter in Bioinformatics and Biomedical Engineering. Lecture Notes in Computer Science, Springer, 9656, 293-303. (EI)
  22. Y.H. Cheng, I.S. Chen, Y.C. Lin, C.W. Tung, H.S. Chang and C.C. Wang* (2016) Attenuation of antigen-specific T helper 1 immunity by Neolitsea hiiranensis and its derived terpenoidsPeerJ, 4, e2758.
  23. Y.K. Chen, C.W. Tung, J.Y. Lee, Y.C. Hung, C.H. Lee, S.H. Chou, H.S. Lin, M.T. Wu and I.C. Wu* (2016) Plasma matrix metalloproteinase 1 improves the detection and survival prediction of esophageal squamous cell carcinomaScientific Reports, 6, 30057.
  24. S.H. Huang, C.W. Tung, F. Fülöp and J.H. Li* (2015) Developing a QSAR model for hepatotoxicity screening of the active compounds in traditional Chinese medicinesFood and Chemical Toxicology, 78, 71-77.
  25. C.W. Tung* (2015) ChemDIS: a chemical-disease inference system based on chemical-protein interactionsJournal of Cheminformatics, 7, 25. (Highly Accessed)
  26. C.W. Tung*, P. Lin and C.C. Wang (2015) Toxicoinformatics Tools for Studying Endocrine Disruption Effects of PesticidesChapter in 104年農藥內分泌干擾作用專題研討會論文集 (蔡韙任 林嬪嬪 費雯綺 李悅怡, ed.), 行政院農業委員會農業藥物毒物試驗所, 67-77.
  27. M. Chen, C.W. Tung, Q. Shi, L. Guo, L. Shi, H. Fang, J. Borlak and W. Tong* (2014) A testing strategy to predict risk for drug-induced liver injury in humans using high-content screen assays and the ‘rule-of-two’ modelArchives of Toxicology, 88(7), 1439-1449.
  28. Y.C. Lin, C.C. Wang and C.W. Tung* (2014) An in silico toxicogenomics approach for inferring potential diseases associated with maleic acidChemico-Biological Interactions, 223(5), 38-44.
  29. C.W. Tung* (2014) Databases for T-cell epitopesMethods in Molecular Biology, 1184, 123-134.
  30. C.W. Tung* (2014) Public databases of plant natural products for computational drug discoveryCurrent Computer-Aided Drug Design, 10(3), 191-196. (Editor Choice Article)
  31. C.W. Tung* and J.L. Jheng (2014) Interpretable prediction of non-genotoxic hepatocarcinogenic chemicalsNeurocomputing, 145, 68-74.
  32. C.W. Tung* (2014) Acquiring decision rules for predicting Ames-negative hepatocarcinogens using chemical-chemical interactionsChapter in Pattern Recognition in Bioinformatics, Lecture Notes in Computer Science, Springer, 8626, 1-9. (EI)
  33. C.W. Tung*, Y.C. Lin, H.S. Chang, C.C. Wang, I.S. Chen, J.L. Jheng and J.H. Li (2014) TIPdb-3D: the three-dimensional structure database of phytochemicals from Taiwan indigenous plantsDatabase (Oxford), 2014, bau055.
  34. W.L. Huang, C.W. Tung, C. Liaw, H.L. Huang and S.Y. Ho* (2014) Rule-based knowledge acquisition method for promoter prediction in human and drosophila speciesThe Scientific World Journal, 2014, 327306.
  35. C.W. Tung* (2013) Prediction of pupylation sites using the composition of k-spaced amino acid pairsJournal of Theoretical Biology, 336, 11-17.
  36. C.W. Tung, M.T. Wu, Y.K. Chen, C.C. Wu, W.C. Chen, H.P. Li, S.H. Chou, D.C. Wu and I.C. Wu* (2013) Identification of biomarkers for esophageal squamous cell carcinoma using feature selection and decision tree methodsThe Scientific World Journal, 2013, 782031.
  37. C.W. Tung* (2013) Prediction of non-genotoxic hepatocarcinogenicity using chemical-protein interactionsChapter in Pattern Recognition in Bioinformatics, Lecture Notes in Computer Science, Springer, 7986, 231-241. (EI)
  38. Y.C. Lin, C.C. Wang, I.S. Chen, J.L. Jheng, J.H. Li and C.W. Tung* (2013) TIPdb: a database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in TaiwanThe Scientific World Journal, 2013, 736386.
  39. C. Liaw, C.W. Tung and S.Y. Ho* (2013) Prediction and analysis of antibody amyloidogenesis from sequencesPLoS One, 8(1), e53235.
  40. C.W. Tung* (2012) PupDB: a database of pupylated proteinsBMC Bioinformatics, 13, 40. (Highly Accessed)
  41. W. Tung, M. Ziehm, A. Kämper, O. Kohlbacher* and S.Y. Ho* (2011) POPISK: T-cell reactivity prediction using support vector machines and string kernelsBMC Bioinformatics, 12, 446. (Highly Accessed)

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