2011年12月-今 中国科学院天津工业生物技术研究所研究员,生物设计中心主任

2005年12月–2011年12月: 英国爱丁堡大学信息学院高级研究科学家

2001年9月–2005年12月:德国生物技术研究中心（GBF）基因组分析部和生物化学工程部博士后

1996年3月–2001年9月: 天津大学化工学院生物化工系助教、讲师

1997年9月–2001年3月: 天津大学化工学院生物化工博士

主要研究方向包括基因组规模代谢网络的构建质控及其结构和功能分析、多约束细胞模型的构建、代谢途径和代谢工程改造策略设计、生物计算设计算法和网站工具开发、基于人工智能的蛋白功能预测和菌种设计等。

科技部合成生物学重点专项项目：高版本模式微生物底盘细胞（课题负责人），2019-2024

科技部绿色制造重点专项项目：重要工业化学品生物制造菌种的新一代网络模型构建与应用（子课题负责人），2021-2024

中国科学院战略性先导科技专项项目：生物大分子合成单细胞生命（子课题负责人），2023-

天津市合成生物技术创新能力提升行动项目，生物计算与设计平台（负责人），2019-2022

中国科学院对外合作重点项目：面向天然产物生物合成的人工细胞（子课题负责人) 2018-2023

中国科学院重点部署项目：二氧化碳的人工生物转化 （子课题负责人) 2016-2018

科技部973计划项目：用合成生物学方法构建生物基材料的合成新途径(课题负责人)，2012-2016

2023年获天津市自然科学奖特等奖

2014年获汤森路透计算机科学领域高被引科学家奖

2006年获天津市自然科学奖二等奖

在包括Science，Nucleic Acids Research, Nature Communication，Metabolic Engineering等高水平刊物发表文章上百篇，总引用超过2000。申请专利和软件著作权十余项。

2.      Yang X, Mao Z, Huang J, Wang R, Dong H, Zhang Y, et al. Improving pathway prediction accuracy of constraints-based metabolic network models by treating enzymes as microcompartments. Synth Syst Biotechnol. 2023;8(4):597-605.

3.      Wu Y, Yuan Q, Yang Y, Liu D, Yang S, Ma H. Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories. Synth Syst Biotechnol. 2023;8(3):498-508.

4.      Wu K, Mao Z, Mao Y, Niu J, Cai J, Yuan Q, et al. ecBSU1: A Genome-Scale Enzyme-Constrained Model of Bacillus subtilis Based on the ECMpy Workflow. Microorganisms. 2023;11(1).

5.      Wang J, Chen Z, Deng X, Yuan Q, Ma H. Engineering Escherichia coli for Poly-β-hydroxybutyrate Production from Methanol. Bioengineering (Basel). 2023;10(4).

6.      Shi Z, Deng R, Yuan Q, Mao Z, Wang R, Li H, et al. Enzyme Commission Number Prediction and Benchmarking with Hierarchical Dual-core Multitask Learning Framework. Research (Wash D C). 2023;6:0153.

7.      Naz S, Liu P, Liu C, Cui M, Ma H. In silico prediction of mutation sites for anthranilate synthase from Serratia marcesens to deregulate tryptophan feedback inhibition. Journal of biomolecular structure & dynamics. 2023:1-11.

8.      Naz S, Liu P, Farooq U, Ma H. Insight into de-regulation of amino acid feedback inhibition: a focus on structure analysis method. Microbial cell factories. 2023;22(1):161.

9.      Mao Z, Yuan Q, Li H, Zhang Y, Huang Y, Yang C, et al. CAVE: a cloud-based platform for analysis and visualization of metabolic pathways. Nucleic acids research. 2023;51(W1):W70-w7.

10.   Cai J, Liao X, Mao Y, Wang R, Li H, Ma H. Designing gene manipulation schedules for high throughput parallel construction of objective strains. Biotechnol J. 2023:e2200578.

11.   Zhang T, Liu P, Wei H, Sun X, Zeng Y, Zhang X, et al. Protein Engineering of Glucosylglycerol Phosphorylase Facilitating Efficient and Highly Regio- and Stereoselective Glycosylation of Polyols in a Synthetic System. ACS Catalysis. 2022;12(24):15715-27.

12.   Yang Y, Mao Y, Wang R, Li H, Liu Y, Cheng H, et al. AutoESD: a web tool for automatic editing sequence design for genetic manipulation of microorganisms. Nucleic acids research. 2022;50(W1):W75-82.

13.   Tian C, Yang J, Liu C, Chen P, Zhang T, Men Y, et al. Engineering substrate specificity of HAD phosphatases and multienzyme systems development for the thermodynamic-driven manufacturing sugars. Nature communications. 2022;13(1):3582.

14.   Niu J, Mao Z, Mao Y, Wu K, Shi Z, Yuan Q, et al. Construction and Analysis of an Enzyme-Constrained Metabolic Model of Corynebacterium glutamicum. Biomolecules. 2022;12(10).

15.   Mao Z, Zhao X, Yang X, Zhang P, Du J, Yuan Q, et al. ECMpy, a Simplified Workflow for Constructing Enzymatic Constrained Metabolic Network Model. Biomolecules. 2022;12(1).

16.   Mao Z, Wang R, Li H, Huang Y, Zhang Q, Liao X, et al. ERMer: a serverless platform for navigating, analyzing, and visualizing Escherichia coli regulatory landscape through graph database. Nucleic acids research. 2022;50(W1):W298-304.

17.   Luo J, Yuan Q, Mao Y, Wei F, Zhao J, Yu W, et al. Reconstruction of a Genome-Scale Metabolic Network for Shewanella oneidensis MR-1 and Analysis of its Metabolic Potential for Bioelectrochemical Systems. Frontiers in bioengineering and biotechnology. 2022;10:913077.

18.   Liao X, Ma H, Tang YJ. Artificial intelligence: a solution to involution of design-build-test-learn cycle. Current opinion in biotechnology. 2022;75:102712.

19.   Yang Y, Mao Y, Liu Y, Wang R, Lu H, Li H, et al. GEDpm-cg: Genome Editing Automated Design Platform for Point Mutation Construction in Corynebacterium glutamicum. Frontiers in bioengineering and biotechnology. 2021;9:768289.

20.   Yang X, Mao Z, Zhao X, Wang R, Zhang P, Cai J, et al. Integrating thermodynamic and enzymatic constraints into genome-scale metabolic models. Metabolic engineering. 2021;67:133-44.

21.   Mao Y, Yuan Q, Yang X, Liu P, Cheng Y, Luo J, et al. Non-natural Aldol Reactions Enable the Design and Construction of Novel One-Carbon Assimilation Pathways in vitro. Frontiers in microbiology. 2021;12:677596.

22.   Gao Y, Yuan Q, Mao Z, Liu H, Ma H. Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis. BMC microbiology. 2021;21(1):292.

23.   Cai T, Sun H, Qiao J, Zhu L, Zhang F, Zhang J, et al. Cell-free chemoenzymatic starch synthesis from carbon dioxide. Science (New York, NY). 2021;373(6562):1523-7.

24.   Lieven C, Beber ME, Olivier BG, Bergmann FT, Ataman M, Babaei P, et al. MEMOTE for standardized genome-scale metabolic model testing. Nature biotechnology. 2020;38(3):272-6.

25.   Yang X, Yuan Q, Luo H, Li F, Mao Y, Zhao X, et al. Systematic design and in vitro validation of novel one-carbon assimilation pathways. Metabolic engineering. 2019;56:142-53.

26.   Mao Z, Ma H. iMTBGO: An Algorithm for Integrating Metabolic Networks with Transcriptomes Based on Gene Ontology Analysis. Current Genomics. 2019;20(4):252-9.

27.   Liu D, Sun H, Ma H. Deciphering Microbiome Related to Rusty Roots of Panax ginseng and Evaluation of Antagonists Against Pathogenic Ilyonectria. Frontiers in microbiology. 2019;10:1350.

28.   Zheng Y, Yuan Q, Luo H, Yang X, Ma H. Engineering NOG-pathway in Escherichia coli for poly-(3-hydroxybutyrate) production from low cost carbon sources. Bioengineered. 2018;9(1):209-13.

29.   Li F, Xie W, Yuan Q, Luo H, Li P, Chen T, et al. Genome-scale metabolic model analysis indicates low energy production efficiency in marine ammonia-oxidizing archaea. AMB Express. 2018;8(1):106.

30.   Zheng Y, Yuan Q, Yang X, Ma H. Engineering Escherichia coli for poly-(3-hydroxybutyrate) production guided by genome-scale metabolic network analysis. Enzyme and microbial technology. 2017;106:60-6.

31.   Yuan Q, Huang T, Li P, Hao T, Li F, Ma H, et al. Pathway-Consensus Approach to Metabolic Network Reconstruction for Pseudomonas putida KT2440 by Systematic Comparison of Published Models. PloS one. 2017;12(1):e0169437.

32.   Yang X, Yuan Q, Zheng Y, Ma H, Chen T, Zhao X. An engineered non-oxidative glycolysis pathway for acetone production in Escherichia coli. Biotechnology letters. 2016;38(8):1359-65.

33.   Meng Q, Zhang Y, Ju X, Ma C, Ma H, Chen J, et al. Production of 5-aminolevulinic acid by cell free multi-enzyme catalysis. Journal of biotechnology. 2016;226:8-13.

34.   Zhang Y, Meng Q, Ma H, Liu Y, Cao G, Zhang X, et al. Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis. Microbial cell factories. 2015;14:86.