中国科学: 化学 2014年 第44卷 第5期

3 Jansson A, Jirstrand M. Biochemical modeling with systems biology graphical notation. Drug Discov Today, 2010, 15: 365–370 4 Joyce AR, Palsson BØ. The model organism as a system: integrating “omics” data sets. Nat Rev Mol Cell Biol, 2006, 7: 198–210

5 Gika GH, Theodoridis GA, Plumb RS, Wilson ID. Current practice of liquid chromatography-mass spectrometry in metabolomics and

metabonomics. J Pharmaceut Biomed Anal, 2014, 87: 12–25

6 Vaint MR, Sommer U. Mass spectrometry based environmental metabolomics: a primer and review. Metabolomics, 2013, 9: 144–158 7 Dettmer K, Aronov PA, Hamock BD. Mass spectrometry-based metabolomics. Mass Spectrom Rev, 2007, 26: 51–78

8 Uehara T, Yokoi A, Aoshima K, Tanaka S, Kadowaki T, Tanaka M, Oda Y. Quantitative phosphorus metabolomics using nanoflow liquid

chromatography-tandem mass spectrometry and culture-derived comprehensive global internal standards. Anal Chem, 2009, 81: 3836–3842 9 Myint KT, Uehara T, Aoshima K, Oda Y. Polar anionic metabolome analysis by nano-LC/MS with a metal chelating agent. Anal Chem,

2009, 81: 7766–7772

10 Boernsen KO, Gatzek S, Imbert G. Controlled protein precipitation in combination with chip-based nanospray infusion mass spectrometry.

An approach for metabolomics profiling of plasma. Anal Chem, 2005, 77: 7255–7264

11 Zenobi R. Single-cell metabolomics: analytical and biological perspectives. Science, 2013, 342: 1201–1211

12 Kirkwood JS, Maier C, Stevens JF. Simultaneous, untargeted metabolic profiling of polar and nonpolar metabolites by LC-Q-TOF mass

spectrometry. Curr Protoc Toxicol, 2013, 56: 4.39.1–4.39.12

13 Moritz F, Forcisi S, Harir M, Kanawati B, Lucio M, Tziotis D, Schmitt-Kopplin P. The potential of ultrahigh resolution MS (FTlCR-MS) in

metabolomics. In: Lammerhofer M, Veckwerth W, Eds. Metabolomics in Practice: Successful Strategies to Generate and Analyze Metabolic Data. Weinheim: Wiley, 2013

14 Shrestha B, Vertes A. In situ metabolic profiling of single cells by laser ablation electrospray ionization mass spectrometry. Anal Chem,

2009, 81: 8265–8271

15 Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD. Analytical and statistical approaches to metabolomics research. J Sep Sci,

2009, 32: 2183–2199

16 Tomita M, KamiK. Systems biology, metabolomics, and cancer metabolism. Science, 2013, 336: 990–991

17 Jain M, Nilsson R, Sharma S, Madhusudhan N, Kitami T, Souza AL, Kafri R, Kirschner MW, Clish CB, Mootha VK. Metabolite profiling

identifies a key role for glycine in rapid cancer cell proliferation. Science, 2012, 336: 1040–1044

18 Dai WD, Huang Q, Yin PY, Li J, Zhou J, Kong HW, Zhao CX, Lu X, Xu GW. Comprehensive and highly sensitive urinary steroid hormone

profiling method based on stable isotope-labeling liquid chromatography-mass spectrometry. Anal Chem, 2012, 84: 10245–10251

19 Wang Y, Lu X, Xu GW. Development of a comprehensive two-dimensional hydrophilic interaction chromatography/quadrupole

time-of-flight mass spectrometry system and its application in separation and identification of saponins from quillaja saponaria. J Chromatogr A, 2008, 1181: 51–59

20 Wang Y, Wang JS, Yao M, Zhao XJ, Fritsche J, Schmitt-Kopplin P, Cai ZW, Wan DF, Lu X, Yang SL, Gu JR, Häring HU, Schleicher ED,

Lehmann R, Xu GW. Metabonomics study on the effects of the ginsenoside Rg3 in a beta-cyclodextrin-based formulation on tumor-bearing rats by a fully automatic hydrophilic interaction/reversed-phase column-switching HPLC-ESI-MS approach. Anal Chem, 2008, 80: 4680–4688

21 Wang SY, Li J, Shi XZ, Qiao LZ, Lu X, Xu GW. A novel stop-flow two-dimensional liquid chromatography-mass spectrometry method for

lipid analysis. J Chromatogr A, 2013, 1321: 65–72

22 Chen SL, Kong HW, Lu X, Li Y, Yin PY, Zeng ZD, Xu GW. Pseudotargeted metabolomics method and its application in serum biomarker

discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry. Anal Chem, 2013, 85: 8326–8333

23 Yang J, Xu GW, Zheng YF, Kong HW, Wang C, Zhao XJ, Pang T. Strategy for metabonomics research based on high-performance liquid

chromatography and liquid chromatography coupled with tandem mass spectrometry. J Chromatogr A, 2005, 1084: 214–221

24 Lin XH, Yang FF, Zhou LN, Yin PY, Kong HW, Xing WB, Lu X, Jia LW, Wang QC, Xu GW. A support vector machine-recursive feature

elimination feature selection method based on artificial contrast variables and mutual information. J Chromatogr B, 2012, 910: 149–155 25 Lin XH, Wang QC, Yin PY, Tang L, Tan YX, Li H, Yan K, Xu GW. A method for handling metabonomics data from liquid

chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection. Metabolomics, 2011, 7: 549–558

26 Li X, Lu X, Tian J, Gao P, Kong HW, Xu GW. Application of fuzzy c-means clustering in data analysis of metabolomics. Anal Chem, 2009,

81: 4468–4475

27 Chen J, Zhao XJ, Fritsche J, Yin PW, Schmitt-Kopplin P, Wang WZ, Lu X, Häring HU, Schleicher ED, Lehmann R, Xu GW. Practical

727