出生年月：1991.09, 男，chengwang@sdu.edu.cn, 13506410587
主要研究方向
系统生物学 (omics study), 生物信息学, 代谢组学, 脂质组学, 质谱 (MS), 核磁共振 (NMR), 机器学习, 癌症与慢性病预防与机理研究。
· 基于核磁共振（NMR) 与质谱 (LC-MS) 仪器平台数据，开发识别新型代谢物方法，搭建代谢组，脂质组学数据库。
· 基于图神经网络，深度挖掘基因组代谢组通路网络，预测神经退行性疾病，癌症发生可能性。
· 基于健康营养行为数据，开发预测与预防慢性病发生的机器学习模型与工具。
学术与工作经历
山东大学 2021.06-至今
国家健康医疗大数据研究院，生物信息大数据中心
公共卫生学院，副研究员，山东大学青年学者未来计划
· 基于高通量质谱代谢组学数据，挖掘与疾病（以食管鳞癌为基础）相关的未知生物标记物及代谢通路，开发快速检测与预防的整合分析方法。
· 基于精神病人群队列代谢组学与基因组学数据，研究精神病药物代谢机理，为临床诊治提供有效分析途径。
· 整合精神病相关代谢组学，脂质组学数据，建立多组学相关联的可视化分析平台。
美国圣路易斯华盛顿大学Washington University in St. Louis, 06/2020-06/2021
博士后研究员Postdoctral Fellow, advisor: Dr. Gary Patti
· 基于机器学习，跨组学（基因组学，蛋白组学，代谢组学）通路分析与预测。
· 基于高分辨率色谱-质谱（LC-MS）进行同位素追踪研究代谢物代谢途径与机理。
· 基于图神经网络（GNN）,对生物系统代谢网络进行深度挖掘。
美国国际教育联盟American Alliance for International Education, 08/2020-06/2021
兼聘讲师Ajunct Professor
制定课程大纲，教授大学机器学习，人工智能课程（中英文），评审人工智能科研项目。
Insight Data Science, San Francisco, CA 01/2020-05/2020
Health Data Science Fellow
基于日常行为与饮食因子预测糖尿病风险
· 基于美国国家健康和营养调查数据，设计和优化了糖尿病风险预测模型。
· 进行了深度的特征变量研究和多个机器学习模型的比较优化，基于Amazon Web Services (AWS)， 用Flask开发了糖尿病风险预测应用。
美国俄亥俄州立大学The Ohio State University, 05/2016-12/2019
Graduate Research Assistant
基于核磁共振（NMR）与高分辨率质谱(MS)的代谢物组分与结构识别
· 通过整合分析高通量核磁共振与质谱数据，建立了识别未知新型代谢物的流程框架，并应用到多种生物样品进行生物标记物识别，如mouse bile, lung tissue。
· 基于多个公开代谢组学数据库, 建立第一个完整的二维核磁共振脂质数据库，实现了脂质代谢物的自动化鉴别。
美国印第安纳大学Indiana University, Bloomington, IN 08/2017-05/2019
Graduate Research Assistant
基于机器学习与统计方法的大数据分析
· 基于自然语言处理处理，开发了预测二手商品价格的机器学习框架。
· 基于卷积神经网路（CNN）和循环神经网络（LSTM） 模型，帮助Google Assistant预测人类语音指令，准确率达94%。
· 优化集成机器学习模型，检测邮件欺诈及垃圾应用，AUC score 达87%。
教育经历
美国俄亥俄州立大学（The Ohio State University）, Columbus, OH
化学博士（生物信息学方向）Ph.D. Physical Chemistry 2014-2019
Advisor: Prof. Rafael Brüschweiler
美国印第安纳大学（Indiana University）, Bloomington, IN
数据科学硕士（人工智能方向），M.S. Data Science 2017-2019
中国石油大学（China University of Petroleum）, Qingdao, China 应用化学学士（计算化学方向）B.S. Applied Chemistry 2009-2013
发表论文
(Co-)First/Corresponding author papers
1. Zhao, L.,+ Wang, C.,+ Peng, S., Zhu, X., Zhang, Z., Zhao, Y., Zhang, J., Zhao, G., Zhang, T.,* Heng, X.* and Zhang, L.,* 2022. Pivotal interplays between fecal metabolome and gut microbiome reveal functional signatures in cerebral ischemic stroke. Journal of Translational Medicine, 20(1), pp.1-15.
2. Chen, R., Li, X., Yang, Y., Song, X., Wang, C.* and Qiao, D.,* 2022. Prediction of protein-protein interaction sites in intrinsically disordered proteins. Frontiers in Molecular Biosciences, 9.
3. Wang, C., Timári, I., Zhang, B., Li, D.W., Leggett, A., Amer, A.O., Bruschweiler-Li, L., Kopec, R.E. and Brüschweiler, R.,* 2020. COLMAR Lipids Web Server and Ultrahigh-Resolution Methods for Two-Dimensional Nuclear Magnetic Resonance-and Mass Spectrometry-Based Lipidomics. Journal of proteome research, 19(4), pp.1674-1683.
4. Wang, C., Zhang, B., Timári, I., Somogyi, Á., Li, D.W., Adcox, H.E., Gunn, J.S., Bruschweiler-Li, L. and Brüschweiler, R.,* 2019. Accurate and efficient determination of unknown metabolites in metabolomics by NMR-based molecular motif identification. Analytical chemistry, 91(24), pp.15686-15693.
5. Leggett, A.,+ Wang, C.,+ Li, D.W., Somogyi, A., Bruschweiler-Li, L. and Brüschweiler, R.,* 2019. Identification of unknown metabolomics mixture compounds by combining NMR, MS, and cheminformatics. Methods in enzymology (Vol. 615, pp. 407-422). Academic Press.
6. Wang, C.,+ He, L.,+ Li, D.W.,+ Bruschweiler-Li, L., Marshall, A.G. * and Brüschweiler, R.,* 2017. Accurate identification of unknown and known metabolic mixture components by combining 3D NMR with fourier transform ion cyclotron resonance tandem mass spectrometry. Journal of proteome research, 16(10), pp.3774-3786.
Co-author papers
7. Yuan, C.,* Wang, C., Zhu, K., Li, S. and Miao, Z.,* 2022. Measles epidemiology and viral nucleoprotein gene evolution in Shandong Province, China. Journal of Medical Virology, 94(10), pp.4926-4933.
8. Wang, Y., Stancliffe, E., Fowle-Grider, R., Wang, R., Wang, C., Schwaiger-Haber, M., Shriver, L.P. and Patti, G.J.,* 2022. Saturation of the mitochondrial NADH shuttles drives aerobic glycolysis in proliferating cells. Molecular cell, 82(17), pp.3270-3283.
9. Hansen, A.L., Kupče, E., Li, D.W., Bruschweiler-Li, L., Wang, C. and Brüschweiler, R.,* 2021. 2D NMR-based metabolomics with HSQC/TOCSY NOAH supersequences. Analytical Chemistry, 93(15), pp.6112-6119.
10. Knobloch, T.J., Ryan, N.M., Bruschweiler-Li, L., Wang, C., Bernier, M.C., Somogyi, A., Yan, P.S., Cooperstone, J.L., Mo, X., Brüschweiler, R.P. and Weghorst, C.M.,* 2019. Metabolic regulation of glycolysis and AMP activated protein kinase pathways during black raspberry-mediated oral cancer chemoprevention. Metabolites, 9(7), p.140.
11. Timári, I., Wang, C., Hansen, A.L., Costa dos Santos, G., Yoon, S.O., Bruschweiler-Li, L. and Brüschweiler, R.,* 2019. Real-time pure shift HSQC NMR for untargeted metabolomics. Analytical chemistry, 91(3), pp.2304-2311.
12. Yuan, J., Zhang, B., Wang, C. and Brüschweiler, R.,* 2018. Carbohydrate background removal in metabolomics samples. Analytical chemistry, 90(24), pp.14100-14104.
13. Oghumu, S., Knobloch, T.J., Weghorst, L.C., Bruschweiler-Li, L., Wang, C., Bruschweiler, R. and Weghorst, C.M.,* 2018. Potential metabolic and molecular mechanisms of black raspberry-mediated oral cancer chemoprevention. Cancer Research, 78(13_Supplement), pp.1270-1270
14. Hansen, A.L., Li, D., Wang, C. and Brüschweiler, R.,* 2017. Absolute Minimal Sampling of Homonuclear 2D NMR TOCSY Spectra for High‐Throughput Applications of Complex Mixtures. Angewandte Chemie, 129(28), pp.8261-8264.
15. Li, D.W., Wang, C. and Brüschweiler, R.,* 2017. Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures. Journal of biomolecular NMR, 68(3), pp.195-202.
学术会议报告
1. 3rd Gateway NMR Conference
Oral presentation, Pittsburgh, PA 11/2018
“Accurate Identification of Known and Unknown Metabolites by Multidimensional NMR and Customized Metabolite Database”
2. 14th Annual Conference of the Metabolomics Society
Oral presentation, Seattle, WA 06/2018
“Accurate Identification of Known and Unknown Metabolites by Multidimensional NMR and Customized Metabolite Database”
3. 2nd Annual Ohio Mass Spectrometry and Metabolomics Symposium
Oral presentation, Columbus, OH 05/2018
“Accurate Identification of Known and Unknown Metabolites in Gallbladder Bile by Multidimensional NMR and Customized Metabolite Database”
4. Inaugural Conference on Food and Nutritional Metabolomics and 14th Annual Ohio Mass Spectrometry Symposium
Poster presentation, Columbus, OH 05/2017
“Facilitating Accurate Identification and Quantitation of Metabolites by Non-uniformly Sampled (NUS) Multi-dimensional NMR”
5. 57th Experimental Nuclear Magnetic Resonance Conference
Poster presentation, Pittsburgh, PA 04/2016
“Non-uniformly Sampled (NUS) Multi-dimensional NMR Spectra and Compressed Sensing: Application to Metabolomics”
其他经历
Metabolites Journal (IF: 4.932, JCR: Q2) 02/2021-至今
审稿人，Reviewer
Appied Science Journal (IF: 2.474, JCR: Q2) 04/2021-至今
审稿人，Reviewer
The Ohio State University, Columbus, OH
Graduate Teaching Assistant, Physical Chemistry 08/2015-05/2016
· 教授基础量子力学，微积分，线性代数与概率论，热力学与动力学。
其它技能
· 语言: 熟练使用英语（听说读写）。
· 编程: 熟练使用Python, Sklearn, Keras, Tensorflow, 数据库SQL 和 non-relational database query (XML, MongoDB).
· 数据分析: 熟练使用可视化数据分析软件，Bayesian inference, generalized linear model (GLM), 机器学习算法(KNN, SVM) 和深度学习建模(CNN, LSTM, FNN), relational and non-relational database.
荣誉
· Food for Health Graduate Student Fellowship, The Ohio State University 2017-2018
· Graduate Student Fellowship for Data Science Program, Indiana University 2017-2019
· Student Travel Award, 14th International Conference of Metabolomics Society 06/2018
