“Omics” in pharmaceutical research:overview, applications, challenges, and future perspectives

YAN Shi-Kai; LIU Run-Hui; JIN Hui-Zi; LIU Xin-Ru; YE Ji; SHAN Lei; ZHANG Wei-Dong

Volume 13 Issue 1

Jan. 2015

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Article Contents

Article Navigation > Chinese Journal of Natural Medicines > 2015 > 13(1): 3-21

Citation:

“Omics” in pharmaceutical research:overview, applications, challenges, and future perspectives

1.
School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China;
2.
School of Pharmacy, Second Military Medical University, Shanghai 200433, China;
3.
Shanghai Institute of Pharmaceutical Industry, Shanghai 200040, China

Corresponding author:
Received Date: 13-Oct.-2014

Fund Project: The work was supported by Professor of Chang Jiang Scholars Program, NSFC (No. 81230090), Shanghai Leading Academic Discipline Project (B906), Key laboratory of drug research for special environments, PLA, Shanghai Engineering Research Center for the Preparation of Bioactive Natural Products (No. 10DZ2251300), the Scientific Foundation of Shanghai, China (Nos. 12401900801, 13401900 101), National Major Project of China (No. 2011ZX09307-002-03) and the National Key Technology R&D Program of China (No. 2012BAI29B06)

Abstract

In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of omics technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These omics are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.
- Omics,
- Genomics,
- Transcriptomics,
- Proteomics,
- Metabolomics,
- Target Discovery,
- Toxicity Assessment,
- Personalized Medicine,
- Traditional Chinese Medicine

References

[1]	Kandpal RP, Saviola B, Felton J. The era of'omics unlimited[J]. Biotechniques, 2009, 46(5):351.
[2]	Cavalli-Sforza LL. The human genome diversity project:past, present and future[J]. Nat Rev Genet, 2005, 6(4):333-340.
[3]	Wang L. Pharmacogenomics:a systems approach[J]. Wiley Interdiscip Rev Syst Biol Med, 2010, 2(1):3-22.
[4]	D'Alessandro A and Zolla L. Pharmacoproteomics:a chess game on a protein field[J]. Drug Discov Today, 2010, 15(23-24):1015-1023.
[5]	Beijer HJ, de Blaey CJ. Hospitalisations caused by adverse drug reactions (ADR):a meta-analysis of observational studies[J]. Pharm World Sci, 2002, 24(2):46-54.
[6]	Garnett MJ, Edelman EJ, Heidorn SJ, et al. Systematic identification of genomic markers of drug sensitivity in cancer cells[J]. Nature, 2012, 483(7391):570-575.
[7]	Visscher H, Ross CJ, Rassekh SR, et al. Pharmacogenomic prediction of anthracycline-induced cardiotoxicity in children[J]. J Clin Oncol, 2012, 30(13):1422-1428.
[8]	Qin J, Li R, Raes J, et al. A human gut microbial gene catalogue established by metagenomic sequencing[J]. Nature, 2010, 464(7285):59-65.
[9]	Poinar HN, Schwarz C, Qi J, et al. Metagenomics to paleogenomics:large-scale sequencing of mammoth DNA[J]. Science, 2006, 311(5759):392-394.
[10]	Ley RE, Backhed F, Turnbaugh P, et al. Obesity alters gut microbial ecology[J]. Proc Natl Acad Sci USA, 2005, 102(31):11070-11075.
[11]	Turnbaugh PJ, Ley RE, Mahowald MA, et al. An obesityassociated gut microbiome with increased capacity for energy harvest[J]. Nature, 2006, 444(7122):1027-1031.
[12]	Le Chatelier E, Nielsen T, Qin J, et al. Richness of human gut microbiome correlates with metabolic markers[J]. Nature, 2013, 500(7464):541-546.
[13]	Manichanh C, Rigottier-Gois L, Bonnaud E, et al. Reduced diversity of faecal microbiota in Crohn's disease revealed by a metagenomic approach[J]. Gut, 2006, 55(2):205-211.
[14]	Siggers RH, Siggers J, Boye M, et al. Early administration of probiotics alters bacterial colonization and limits diet-induced gut dysfunction and severity of necrotizing enterocolitis in preterm pigs[J]. J Nutr, 2008, 138(8):1437-1444.
[15]	Scanlan PD, Shanahan F, Clune Y, et al. Culture-independent analysis of the gut microbiota in colorectal cancer and polyposis[J]. Environ Microbiol, 2008, 10(3):789-798.
[16]	Larsen N, Vogensen FK, van den Berg FW, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults[J]. PLoS One, 2010, 5(2):e9085.
[17]	Laird PW. Principles and challenges of genome-wide DNA methylation analysis[J]. Nat Rev Genet, 2010, 11(3):191-203.
[18]	Jenuwein T, Allis CD. Translating the histone code[J]. Science, 2001, 293(5532):1074-1080.
[19]	Hake SB, Allis CD. Histone H3 variants and their potential role in indexing mammalian genomes:the H3 barcode hypothesis [J]. Proc Natl Acad Sci USA, 2006, 103(17):6428-6435.
[20]	Grewal SI, Elgin SC. Transcription and RNA interference in the formation of heterochromatin[J]. Nature, 2007, 447(7143):399-406.
[21]	Fraser P, Bickmore W. Nuclear organization of the genome and the potential for gene regulation[J]. Nature, 2007, 447(7143):413-417.
[22]	Sandoval J, Esteller M. Cancer epigenomics:beyond genomics[J]. Curr Opin Genet Dev, 2012, 22(1):50-55.
[23]	Bradbury J. Human epigenome project-up and running[J]. PLoS Biol, 2003, 1(3):e82.
[24]	Kulis M, Esteller M. DNA methylation and cancer[J]. Adv Genet, 2010, 70:27-56.
[25]	Strahl BD, Allis CD. The language of covalent histone modifications[J]. Nature, 2000, 403(6765):41-45.
[26]	Maskos U, Southern EM. Oligonucleotide hybridizations on glass supports:a novel linker for oligonucleotide synthesis and hybridization properties of oligonucleotides synthesised in situ[J]. Nucleic Acids Res, 1992, 20(7):1679-1684.
[27]	Velculescu VE, Zhang L, Vogelstein B, et al. Serial analysis of gene expression[J]. Science, 1995, 270(5235):484-487.
[28]	Brenner S, Johnson M, Bridgham J, et al. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays[J]. Nat Biotechnol, 2000, 18(6):630-634.
[29]	Morin R, Bainbridge M, Fejes A, et al. Profiling the HeLa S3 transcriptome using randomly primed cDNA and massively parallel short-read sequencing[J]. Biotechniques, 2008, 45(1):81-94.
[30]	Chu Y, Corey DR. RNA sequencing:platform selection, experimental design, and data interpretation[J]. Nucleic Acid Ther, 2012, 22(4):271-274.
[31]	Wang Z, Gerstein M, Snyder M. RNA-Seq:a revolutionary tool for transcriptomics[J]. Nat Rev Genet, 2009, 10(1):57-63.
[32]	Sutherland GT, Janitz M, Kril JJ. Understanding the pathogenesis of Alzheimer's disease:will RNA-Seq realize the promise of transcriptomics?[J]. J Neurochem, 2011, 116(6):937-946.
[33]	Fehlbaum-Beurdeley P, Sol O, Desire L, et al. Validation of AclarusDx, a blood-based transcriptomic signature for the diagnosis of Alzheimer's disease[J]. J Alzheimers Dis, 2012, 32(1):169-181.
[34]	Voineagu I, Wang X, Johnston P, et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology[J]. Nature, 2011, 474(7351):380-384.
[35]	Heidecker B, Hare JM. The use of transcriptomic biomarkers for personalized medicine[J]. Heart Fail Rev, 2007, 12(1):1-11.
[36]	Cui Y, Paules RS. Use of transcriptomics in understanding mechanisms of drug-induced toxicity[J]. Pharmacogenomics, 2010, 11(4):573-585.
[37]	Kandoth C, Schultz N, Cherniack AD, et al. Integrated genomic characterization of endometrial carcinoma[J]. Nature, 2013, 497(7447):67-73.
[38]	Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups[J]. Nature, 2012, 486(7403):346-352.
[39]	Labb RM, Irimia M, Currie KW, et al. A comparative transcriptomic analysis reveals conserved features of stem cell pluripotency in planarians and mammals[J]. Stem Cells, 2012, 30(8):1734-1745.
[40]	Wilkins MR, Pasquali C, Appel RD, et al. From proteins to proteomes:large scale protein identification by two-dimensional electrophoresis and amino acid analysis[J]. Biotechnology, 1996, 14(1):61-65.
[41]	Anderson NL, Anderson NG. Proteome and proteomics:New technologies, new concepts, and new words[J]. Electrophoresis, 1998, 19(11):1853-1861.
[42]	Blackstock WP, Weir MP. Proteomics:quantitative and physical mapping of cellular proteins[J]. Trends Biotechnol, 1999, 17(3):121-127.
[43]	Marouga R, David S, Hawkins E. The development of the DIGE system:2D fluorescence difference gel analysis technology[J]. Anal Bioanal Chem, 2005, 382(3):669-678.
[44]	Tannu NS, Hemby SE. Two-dimensional fluorescence difference gel electrophoresis for comparative proteomics profiling[J]. Nat Protoc, 2006, 1(4):1732-1742.
[45]	Bennett KL, Funk M, Tschernutter M, et al. Proteomic analysis of human cataract aqueous humour:Comparison of one-dimensional gel LCMS with two-dimensional LCMS of unlabelled and iTRAQ(R)-labelled specimens[J]. J Proteomics, 2011, 74(2):151-166.
[46]	Irar S, Brini F, Masmoudi K, et al. Combination of 2DE and LC for plant proteomics analysis[J]. Methods Mol Biol, 2014, 1072:131-140.
[47]	Stalmach A, Albalat A, Mullen W, et al. Recent advances in capillary electrophoresis coupled to mass spectrometry for clinical proteomic applications[J]. Electrophoresis, 2013, 34(11):1452-1464.
[48]	Asara J, Christofk H, Freimark L, et al. A label-free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen[J]. Proteomics, 2008, 8(5):994-999.
[49]	Gygi SP, Rist B, Gerber SA, et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags[J]. Nat Biotechnol, 1999, 17(10):994-999.
[50]	Zieske LR. A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies[J]. J Exp Bot, 2006, 57(7):1501-1508.
[51]	Schwanhusser B, Gossen M, Dittmar G, et al. Global analysis of cellular protein translation by pulsed SILAC[J]. Proteomics, 2009, 9(1):205-209.
[52]	Chen J, Khne T, Rcken C, et al. Proteome analysis of gastric cancer metastasis by two-dimensional gel electrophoresis and matrix assisted laser desorption/ionization-mass spectrometry for identification of metastasis-related proteins[J]. J Proteome Res, 2004, 3(5):1009-1016.
[53]	Ping S, Wang S, Zhang J, et al. Effect of all-trans-retinoic acid on mRNA binding protein p62 in human gastric cancer cells[J]. Int J Biochem Cell Biol, 2005, 37(3):616-627.
[54]	Poon TC, Sung JJ, Chow SM, et al. Diagnosis of gastric cancer by serum proteomic fingerprinting[J]. Gastroenterology, 2006, 130(6):1858-1864.
[55]	Mu AK, Chan YS, Kang SS, et al. Detection of host-specific immunogenic proteins in the saliva of patients with oral squamous cell carcinoma[J]. J Immunoassay Immunochem, 2014, 35(2):183-193.
[56]	Kubota D, Yoshida A, Kikuta K, et al. Proteomic approach to gastrointestinal stromal tumor identified prognostic biomarkers[J]. J Proteomics Bioinform, 2014, 7(1):10-16.
[57]	Lim YP. Mining the tumor phosphoproteome for cancer markers[J]. Clin Cancer Res, 2005, 11(9):3163-3169.
[58]	Yu LR, Issaq HJ, Veenstra TD. Phosphoproteomics for the discovery of kinases as cancer biomarkers and drug targets[J]. Proteomics Clin Appl, 2007, 1(9):1042-1057.
[59]	Bolger SJ, Hurtado PA, Hoffert JD, et al. Quantitative phosphoproteomics in nuclei of vasopressin-sensitive renal collecting duct cells[J]. Am J Physiol Cell Physiol, 2012, 303(10):1006-1020.
[60]	Rinschen MM, Yu MJ, Wang G, et al. Quantitative phosphoproteomic analysis reveals vasopressin V2-receptor-dependent signaling pathways in renal collecting duct cells[J]. Proc Natl Acad Sci USA, 2010, 107(8):3882-3887.
[61]	Zhao B, Knepper MA, Chou CL, et al. Large-scale phosphotyrosine proteomic profiling of rat renal collecting duct epithelium reveals predominance of proteins involved in cell polarity determination[J]. Am J Physiol Cell Physiol, 2012, 302(1):27-45.
[62]	Feric M, Zhao B, Hoffert JD, et al. Large-scale phosphoproteomic analysis of membrane proteins in renal proximal and distal tubule[J]. Am J Physiol Cell Physiol, 2011, 300(4):755-770.
[63]	Gonzales PA, Pisitkun T, Hoffert JD, et al. Large-scale proteomics and phosphoproteomics of urinary exosomes[J]. J Am Soc Nephrol, 2009, 20(2):363-379.
[64]	Hoffert JD, Pisitkun T, Wang G, et al. Quantitative phosphoproteomics of vasopressin-sensitive renal cells:regulation of aquaporin-2 phosphorylation at two sites[J]. Proc Natl Acad Sci USA, 2006, 103(18):7159-7164.
[65]	Tissot B, North SJ, Ceroni A, et al. Glycoproteomics:past, present and future[J]. FEBS Lett, 2009, 583(11):1728-1735.
[66]	Hagglund P, Bunkenborg J, Elortza F, et al. A new strategy for identification of N-glycosylated proteins and unambiguous assignment of their glycosylation sites using HILIC enrichment and partial deglycosylation[J]. J Proteome Res, 2004, 3(3):556-566.
[67]	Yang Z, Hancock WS. Approach to the comprehensive analysis of glycoproteins isolated from human serum using a multi-lectin affinity column[J]. J Chromatogr A, 2004, 1053(1-2):79-88.
[68]	Hirabayashi J, Hayama K, Kaji H, et al. Affinity capturing and gene assignment of soluble glycoproteins produced by the nematode Caenorhabditis elegans[J]. J Biochem, 2002, 132(1):103-114.
[69]	Madera M, Mechref Y, Klouckova I, et al. Semiautomated high-sensitivity profiling of human blood serum glycoproteins through lectin preconcentration and multidimensional chromatography/tandem mass spectrometry[J]. J Proteome Res, 2006, 5(9):2348-2363.
[70]	Kameyama A, Kikuchi N, Nakaya S, et al. A strategy for identification of oligosaccharide structures using observational multistage mass spectral library[J]. Anal Chem, 2005, 77(15):4719-4725.
[71]	Yen TY, Haste N, Timpe LC, et al. Using a cell line breast cancer progression system to identify biomarker candidates[J]. J Proteomics, 2014, 96:173-183.
[72]	Ahn JM, Sung HJ, Yoon YH, et al. Integrated glycoproteomics demonstrates fucosylated serum paraoxonase 1 alterations in small cell lung cancer[J]. Mol Cell Proteomics, 2014, 13(1):30-48.
[73]	Bones J, Byrne JC, O'Donoghue N, et al. Glycomic and glycoproteomic analysis of serum from patients with stomach cancer reveals potential markers arising from host defense response mechanisms[J]. J Proteome Res, 2011, 10(3):1246-1265.
[74]	Wu J, Xie X, Liu Y, et al. Identification and confirmation of differentially expressed fucosylated glycoproteins in the serum of ovarian cancer patients using a lectin array and LC-MS/MS[J]. J Proteome Res, 2012, 11(9):4541-4552.
[75]	Ito K, Kuno A, Ikehara Y, et al. LecT-Hepa, a glyco-marker derived from multiple lectins, as a predictor of liver fibrosis in chronic hepatitis C patients[J]. Hepatology, 2012, 56(4):1448-1456.
[76]	Butterfield DA, Owen JB. Lectin-affinity chromatography brain glycoproteomics and Alzheimer disease:insights into protein alterations consistent with the pathology and progression of this dementing disorder[J]. Proteomics Clin Appl, 2011, 5(1-2):50-56.
[77]	Strassberger V, Fugmann T, Neri D, et al. Chemical proteomic and bioinformatic strategies for the identification and quantification of vascular antigens in cancer[J]. J Proteomics, 2010, 73(10):1954-1973.
[78]	Adam GC, Sorensen EJ, Cravatt BF. Chemical strategies for functional proteomics[J]. Mol Cell Proteomics, 2002, 1(10):781-790.
[79]	Terstappen GC, Schlupen C, Raggiaschi R, et al. Target deconvolution strategies in drug discovery[J]. Nat Rev Drug Discov, 2007, 6(11):891-903.
[80]	Lomenick B, Olsen RW, Huang J. Identification of direct protein targets of small molecules[J]. ACS ChemBiol, 2010, 6(1):34-46.
[81]	Sato S-i, Murata A, Shirakawa T, et al. Biochemical target isolation for novices:affinity-based strategies[J]. Chem Biol, 2010, 17(6):616-623.
[82]	Lomenick B, Hao R, Jonai N, et al. Target identification using drug affinity responsive target stability (DARTS)[J]. Proc Natl Acad Sci USA, 2009, 106(51):21984-21989.
[83]	Huang J, Zhu H, Haggarty SJ, et al. Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips[J]. Proc Natl Acad Sci USA, 2004, 101(47):16594-16599.
[84]	Barabasi A-L, Oltvai ZN. Network biology:understanding the cell's functional organization[J]. Nat Rev Genet, 2004, 5(2):101-113.
[85]	Greenbaum DC, Baruch A, Grainger M, et al. A role for the protease falcipain 1 in host cell invasion by the human malaria parasite[J]. Science, 2002, 298(5600):2002-2006.
[86]	Zhang XW, Yan XJ, Zhou ZR, et al. Arsenic trioxide controls the fate of the PML-RARalpha oncoprotein by directly binding PML[J]. Science, 2010, 328(5975):240-243.
[87]	Nicholson JK. Global systems biology, personalized medicine and molecular epidemiology[J]. Mol Syst Biol, 2006, 2:52
[88]	Trygg J, Holmes E, Lundstedt T. Chemometrics in metabonomics[J]. J Proteome Res, 2007, 6(2):469-479.
[89]	Smith CA, Want EJ, O'Maille G, et al. XCMS:Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification[J]. Anal Chem, 2006, 78(3):779-787.
[90]	Tautenhahn R, Patti GJ, Rinehart D, et al. XCMS Online:a web-based platform to process untargeted metabolomic data[J]. Anal Chem, 2012, 84(11):5035-5039.
[91]	Katajamaa M, Miettinen J, Oreič M. MZmine:toolbox for processing and visualization of mass spectrometry based molecular profile data[J]. Bioinformatics, 2006, 22(5):634-636.
[92]	Lommen A. MetAlign:interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing[J]. Anal Chem, 2009, 81(8):3079-3086.
[93]	Baran R, Kochi H, Saito N, et al. MathDAMP:a package for differential analysis of metabolite profiles[J]. BMC Bioinformatics, 2006, 7:530.
[94]	Robertson DG. Metabonomics in toxicology:a review[J]. Toxicol Sci, 2005, 85(2):809-822.
[95]	Sabatine MS, Liu E, Morrow DA, et al. Metabolomic identification of novel biomarkers of myocardial ischemia[J]. Circulation, 2005, 112(25):3868-3875.
[96]	Zhang A, Sun H, Yan G, et al. Metabolomics in diagnosis and biomarker discovery of colorectal cancer[J]. Cancer Lett, 2014, 345(1):17-20.
[97]	Denkert C, Budczies J, Weichert W, et al. Metabolite profiling of human colon carcinoma--deregulation of TCA cycle and amino acid turnover[J]. Mol Cancer, 2008, 7(72):1476-4598.
[98]	Clayton TA, Lindon JC, Cloarec O, et al. Pharmaco-metabonomic phenotyping and personalized drug treatment[J]. Nature, 2006, 440(7087):1073-1077.
[99]	Wang X, Yan SK, Dai WX, et al. A metabonomic approach to chemosensitivity prediction of cisplatin plus 5-fluorouracil in a human xenograft model of gastric cancer[J]. Int J Cancer, 2010, 127(12):2841-2850.
[100]	Amacher DE. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity[J]. Toxicol Appl Pharmacol, 2010, 245(1):134-142.
[101]	Klawitter J, Haschke M, Kahle C, et al. Toxicodynamic effects of ciclosporin are reflected by metabolite profiles in the urine of healthy individuals after a single dose[J]. Br J Clin Pharmacol, 2010, 70(2):241-251.
[102]	Ichikawa W. Prediction of clinical outcome of fluoropyrimidine-based chemotherapy for gastric cancer patients, in terms of the 5-fluorouracil metabolic pathway[J]. Gastric Cancer, 2006, 9(3):145-155.
[103]	Howells DW, Sena ES, O'Collins V, et al. Improving the efficiency of the development of drugs for stroke[J]. Int J Stroke, 2012, 7(5):371-377.
[104]	Han X, Gross RW. Global analyses of cellular lipidomes directly from crude extracts of biological samples by ESI mass spectrometry:a bridge to lipidomics[J]. J Lipid Res, 2003, 44(6):1071-1079.
[105]	Wenk MR. The emerging field of lipidomics[J]. Nat Rev Drug Discov, 2005, 4(7):594-610.
[106]	Watson AD. Thematic review series:systems biology approaches to metabolic and cardiovascular disorders. Lipidomics:a global approach to lipid analysis in biological systems[J]. J Lipid Res, 2006, 47(10):2101-2111.
[107]	Bligh EG, Dyer WJ. A rapid method of total lipid extraction and purification[J]. Can J Biochem Physiol, 1959, 37(8):911-917.
[108]	Wenk MR. Lipidomics in drug and biomarker development[J]. Expert Opin Drug Discov, 2006, 1(7):723-736.
[109]	Marechal E, Riou M, Kerboeuf D, et al. Membrane lipidomics for the discovery of new antiparasitic drug targets[J]. Trends Parasitol, 2011, 27(11):496-504.
[110]	Adibhatla RM, Hatcher JF and Dempsey RJ. Lipids and lipidomics in brain injury and diseases[J]. Aaps J, 2006, 8(2):E314-321.
[111]	Bilder RM, Sabb FW, Cannon TD, et al. Phenomics:the systematic study of phenotypes on a genome-wide scale[J]. Neuroscience, 2009, 164(1):30-42.
[112]	Joy T, Hegele RA. Genetics of metabolic syndrome:is there a role for phenomics?[J]. Curr Atheroscler Rep, 2008, 10(3):201-208.
[113]	Finkel E. With 'Phenomics', plant scientists hope to shift breeding into overdrive[J]. Science, 2009, 325(5939):380-381.
[114]	Pizza M, Scarlato V, Masignani V, et al. Identification of vaccine candidates against serogroup B meningococcus by whole-genome sequencing[J]. Science, 2000, 287(5459):1816-1820.
[115]	Bambini S, Rappuoli R. The use of genomics in microbial vaccine development[J]. Drug Discov Today, 2009, 14(5-6):252-260.
[116]	He Y. Omics-based systems vaccinology for vaccine target identification[J]. Drug Develop Res, 2012, 73(8):559-568.
[117]	Bulman A, Neagu M, Constantin C. Immunomics in skin cancer-improvement in diagnosis, Prognosis and Therapy Monitoring[J]. Curr Proteomics, 2013, 10(3):202.
[118]	Haraguchi H. Metallomics as integrated biometal science[J]. J Anal At Spectrom, 2004, 19(1):5-14.
[119]	Szpunar J. Advances in analytical methodology for bioinorganic speciation analysis:metallomics, metalloproteomics and heteroatom-tagged proteomics and metabolomics[J]. Analyst, 2005, 130(4):442-465.
[120]	Chry CC, Gnther D, Cornelis R, et al. Detection of metals in proteins by means of polyacrylamide gel electrophoresis and laser ablation-inductively coupled plasma-mass spectrometry:Application to selenium[J]. Electrophoresis, 2003, 24(19-20):3305-3313.
[121]	Carmona A, Cloetens P, Devs G, et al. Nano-imaging of trace metals by synchrotron X-ray fluorescence into dopaminergic single cells and neurite-like processes[J]. J Anal At Spectrom, 2008, 23(8):1083-1088.
[122]	Gonzlez-Fernndez M, Garca-Barrera T, Arias-Borrego A, et al. Metallomics integrated with proteomics in deciphering metal-related environmental issues[J]. Biochimie, 2009, 91(10):1311-1317.
[123]	Sun X, Tsang C-N, Sun H. Identification and characterization of metallodrug binding proteins by (metallo) proteomics[J]. Metallomics, 2009, 1(1):25-31.
[124]	Yan XD, Pan LY, Yuan Y, et al. Identification of platinumresistance associated proteins through proteomic analysis of human ovarian cancer cells and their platinum-resistant sublines[J]. J Proteome Res, 2007, 6(2):772-780.
[125]	Schooley K, Zhu P, Dower SK, et al. Regulation of nuclear translocation of nuclear factor-kappaB relA:evidence for complex dynamics at the single-cell level[J]. Biochem J, 2003, 369(Pt 2):331-339.
[126]	Valet G. Cytomics as a new potential for drug discovery[J]. Drug Discov Today, 2006, 11(17):785-791.
[127]	Jang YJ, Jeon OH, Kim DS. Saxatilin, a snake venom disintegrin, regulates platelet activation associated with human vascular endothelial cell migration and invasion[J]. J Vasc Res, 2007, 44(2):129-137.
[128]	Shanks RH, Rizzieri DA, Flowers JL, et al. Preclinical evaluation of gemcitabine combination regimens for application in acute myeloid leukemia[J]. Clin Cancer Res, 2005, 11(11):4225-4233.
[129]	Danku JM, Gumaelius L, Baxter I, et al. A high-throughput method for Saccharomyces cerevisiae (yeast) ionomics[J]. J Anal At Spectrom, 2009, 24(1):103-107.
[130]	Young LW, Westcott ND, Attenkofer K, et al. A high-throughput determination of metal concentrations in whole intact Arabidopsis thaliana seeds using synchrotron-based X-ray fluorescence spectroscopy[J]. J Synchrotron Radiat, 2006, 13(4):304-313.
[131]	Eide DJ, Clark S, Nair TM, et al. Characterization of the yeast ionome:a genome-wide analysis of nutrient mineral and trace element homeostasis in Saccharomyces cerevisiae[J]. Genome Biol, 2005, 6(9):R77.
[132]	Ziegler G, Terauchi A, Becker A, et al. Ionomic screening of field-grown soybean identifies mutants with altered seed elemental composition[J]. The Plant Genome, 2013, 6(2):1-9.
[133]	Sanchez C, Lachaize C, Janody F, et al. Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an internet database[J]. Nucleic Acids Res, 1999, 27(1):89-94.
[134]	Sakurai T, Amemiya A, Ishii M, et al. Orexins and orexin receptors:a family of hypothalamic neuropeptides and G protein-coupled receptors that regulate feeding behavior[J]. Cell, 1998, 92(4):573-585.
[135]	Maglott D, Ostell J, Pruitt KD, et al. Entrez Gene:genecentered information at NCBI[J]. Nucleic Acids Res, 2007, 35(S1):D26-D31.
[136]	Rhodes DR, Kalyana-Sundaram S, Mahavisno V, et al. Oncomine 3.0:genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles[J]. Neoplasia, 2007, 9(2):166-180.
[137]	Gao Z, Li H, Zhang H, et al. PDTD:a web-accessible protein database for drug target identification[J]. BMC Bioinformatics, 2008, 9(104):1471-2105.
[138]	Jayapal M, Melendez AJ. DNA microarray technology for target identification and validation[J]. Clin Exp Pharm Physiol, 2006, 33(5-6):496-503.
[139]	Ricciarelli R, d'Abramo C, Massone S, et al. Microarray analysis in Alzheimer's disease and normal aging[J]. IUBMB life, 2004, 56(6):349-354.
[140]	Grnblatt E, Mandel S, Maor G, et al. Gene expression analysis in N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mice model of Parkinson's disease using cDNA microarray:effect of Rapomorphine[J].J Neurochem, 2001, 78(1):1-12.
[141]	Stam RW, den Boer ML, Meijerink JP, et al. Differential mRNA expression of Ara-C-metabolizing enzymes explains Ara-C sensitivity in MLL gene-rearranged infant acute lymphoblastic leukemia[J]. Blood, 2003, 101(4):1270-1276.
[142]	Fong D, Spizzo G, Gostner JM, et al. TROP2:a novel prognostic marker in squamous cell carcinoma of the oral cavity[J]. Mod Pathol, 2007, 21(2):186-191.
[143]	Keskin O, Gursoy A, Ma B, et al. Towards drugs targeting multiple proteins in a systems biology approach[J]. Curr Top Med Chem, 2007, 7(10):943-951.
[144]	Gresham V, McLeod HL. Genomics:Applications in mechanism elucidation[J]. Adv Drug Deliv Rev, 2009, 61(5):369-374.
[145]	Attia SM, Ahmad SF, Zoheir KM, et al. Genotoxic evaluation of chloroacetonitrile in murine marrow cells and effects on DNA damage repair gene expressions[J]. Mutagenesis, 2014, 29(1):55-62.
[146]	Wetmore BA, Merrick BA. Toxicoproteomics:proteomics applied to toxicology and pathology[J]. Toxicol Pathol, 2004, 32(6):619-642.
[147]	Gresham V, McLeod HL. Genomics:applications in mechanism elucidation[J]. Adv Drug Deliv Rev, 2009, 61(5):369-374.
[148]	Bouhifd M, Hartung T, Hogberg HT, et al. Review:toxicometabolomics[J]. J Appl Toxicol, 2013, 33(12):1365-1383.
[149]	Nicholson JK, Everett JR, Lindon JC. Longitudinal pharmacometabonomics for predicting patient responses to therapy:drug metabolism, toxicity and efficacy[J]. Expert Opin Drug Metab Toxicol, 2012, 8(2):135-139.
[150]	Soga T, Baran R, Suematsu M, et al. Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption[J]. J Bio Chem, 2006, 281(24):16768-16776.
[151]	Giacomini KM, Krauss RM, Roden DM, et al. When good drugs go bad[J]. Nature, 2007, 446(7139):975-977.
[152]	Loscalzo J, Kohane I, Barabasi AL. Human disease classification in the postgenomic era:a complex systems approach to human pathobiology[J]. Mol Syst Biol, 2007, 3(124):10.
[153]	Johnson JA. Advancing management of hypertension through pharmacogenomics[J]. Ann Med, 2012, 44(S1):S17-S22.
[154]	Gupta S and Awasthi S. Pharmacogenomics of pediatric asthma[J]. Indian J Hum Genet, 2010, 16(3):111-118.
[155]	Aslibekyan S, Straka RJ, Irvin MR, et al. Pharmacogenomics of high-density lipoprotein-cholesterol-raising therapies[J]. Expert Rev Cardiovasc Ther, 2013, 11(3):355-364.
[156]	Ingle JN. Pharmacogenomics of endocrine therapy in breast cancer[J]. J Hum Genet, 2013, 58(6):306-312.
[157]	Lee W, Lockhart AC, Kim RB, et al. Cancer pharmacogenomics:powerful tools in cancer chemotherapy and drug development[J]. The Oncologist, 2005, 10(2):104-111.
[158]	Ferrari P. Pharmacogenomics:a new approach to individual therapy of hypertension?[J]. Curr Opin Nephrol Hypertens, 1998, 7(2):217-222.
[159]	Hancox RJ, Sears MR, Taylor DR. Polymorphism of the beta2-adrenoceptor and the response to long-term beta2-agonist therapy in asthma[J]. Eur Respir J, 1998, 11(3):589-593.
[160]	Holmes E, Nicholson JK, Tranter G. Metabonomic characterization of genetic variations in toxicological and metabolic responses using probabilistic neural networks[J]. Chem Res Toxicol, 2001, 14(2):182-191.
[161]	Nicholson JK, Wilson ID, Lindon JC. Pharmacometabonomics as an effector for personalized medicine[J]. Pharmacogenomics, 2011, 12(1):103-111.
[162]	van Wietmarschen HA, der Greef Jv, Schron Y, et al. Evaluation of symptom, clinical chemistry and metabolomics profiles during Rehmannia six formula (R6) treatment:An integrated and personalized data analysis approach[J]. J Ethnopharmacol, 2013, 150(3):851-859.
[163]	Keun HC, Sidhu J, Pchejetski D, et al. Serum molecular signatures of weight change during early breast cancer chemotherapy[J]. Clin Canc Res, 2009, 15(21):6716-6723.
[164]	Klayman DL. Qinghaosu (artemisinin):an antimalarial drug from China[J]. Science, 1985, 228(4703):1049-1055.
[165]	Chen GQ, Shi XG, Tang W, et al. Use of arsenic trioxide (As2O3) in the treatment of acute promyelocytic leukemia (APL):I. As2O3 exerts dose-dependent dual effects on APL cells[J]. Blood, 1997, 89(9):3345-3353.
[166]	Ma WH, Lu Y, Huang H, et al. Schisanwilsonins A-G and related anti-HBV lignans from the fruits of Schisandra wilsoniana[J]. Bioorg Med Chem Lett, 2009, 19(17):4958-4962.
[167]	Ma X, Gang DR. In vitro production of huperzine A, a promising drug candidate for Alzheimer's disease[J]. Phytochemistry, 2008, 69(10):2022-2028.
[168]	Qiu J. Traditional medicine:a culture in the balance[J]. Nature, 2007, 448(7150):126-128.
[169]	Zhang YB, Wang J, Wang ZT, et al. DNA microarray for identification of the herb of Dendrobium species from Chinese medicinal formulations[J]. Planta Med, 2003, 69(12):1172-1174.
[170]	Wang GL, Chen CB, Gao JM, et al. Investigation on the molecular mechanisms of anti-hepatocarcinoma herbs of traditional Chinese medicine by cell cycle microarray[J]. China J Chin Mater Med, 2005, 30(1):50-54.
[171]	Zhang ZJ, Li P, Wang Z, et al. A comparative study on the individual and combined effects of baicalin and jasminoidin on focal cerebral ischemia-reperfusion injury[J]. Brain Res, 2006, 1123(1):188-195.
[172]	Hara A, Iizuka N, Hamamoto Y, et al. Molecular dissection of a medicinal herb with anti-tumor activity by oligonucleotide microarray[J]. Life Sci, 2005, 77(9):991-1002.
[173]	Yue QX, Cao ZW, Guan SH, et al. Proteomics characterization of the cytotoxicity mechanism of ganoderic acid D and computer-automated estimation of the possible drug target network[J]. Mol Cell Proteomics, 2008, 7(5):949-961.
[174]	Yue QX, Song XY, Ma C, et al. Effects of triterpenes from Ganoderma lucidum on protein expression profile of HeLa cells[J]. Phytomedicine, 2010, 17(8-9):606-613.
[175]	Wang X, Chen Y, Han QB, et al. Proteomic identification of molecular targets of gambogic acid:role of stathmin in hepatocellular carcinoma[J]. Proteomics, 2009, 9(2):242-253.
[176]	Chen M, Su M, Zhao L, et al. Metabonomic study of aristolochic acid-induced nephrotoxicity in rats[J]. J Proteome Res, 2006, 5(4):995-1002.
[177]	Li WX, Tang YP, Guo JM, et al. Comparative metabolomics analysis on hematopoietic functions ofherb pair Gui-Xiong by ultra-high-performance liquidchromatography coupled to quadrupole time-of-flight massspectrometry and pattern recognition approach[J]. J Chromatogr A, 2014, 1346:49-56.
[178]	Li L, Wang J, Ren J, et al. Metabonomics analysis of the urine of rats with Qi deficiency and blood stasis syndrome based on NMR techniques[J]. Chin Sci Bull, 2007, 52(22):3068-3073.
[179]	Wang X, Zhang A, Han Y, et al. Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease[J]. Mol Cell Proteomics, 2012, 11(8):370-380.
[180]	Droste P, Miebach S, Niedenfhr S, et al. Visualizing multi-omics data in metabolic networks with the software Omix-a case study[J]. Biosystems, 2011, 105(2):154-161.
[181]	Haoudi A, Bensmail H. Bioinformatics and data mining in proteomics[J]. Expert Rev Proteomics, 2006, 3(3):333-343.
[182]	Wolstencroft K, Haines R, Fellows D, et al. The Taverna workflow suite:designing and executing workflows of Web Services on the desktop, web or in the cloud[J]. Nucleic Acids Res, 2013, 41(Web Server issue):W557-561.
[183]	McIntyre RS, Cha DS, Jerrell JM, et al. Advancing biomarker research:utilizing 'Big Data' approaches for the characterization and prevention of bipolar disorder[J]. BipolarDisord, 2014, 16(5):531-547.
[184]	Hassani S, Martens H, Qannari EM, et al. Analysis of-omics data:Graphical interpretation- and validation tools in multiblock methods[J]. Chemometr Intell Lab Syst, 2010, 104(1):140-153.
[185]	Zhang Z, Chen J, Guo F, et al. A high-temporal resolution technology for dynamic proteomic analysis based on 35S labeling[J]. PLoS One, 2008, 3(8):e2991.
[186]	Chen R, Mias GI, Li-Pook-Than J, et al. Personal omics profiling reveals dynamic molecular and medical phenotypes[J]. Cell, 2012, 148(6):1293-1307.
[187]	Nakanishi Y, Fukuda S, Chikayama E, et al. Dynamic omics approach identifies nutrition-mediated microbial interactions[J]. J Proteome Res, 2010, 10(2):824-836.

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

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“Omics” in pharmaceutical research:overview, applications, challenges, and future perspectives

Corresponding author:

1. School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China;

2. School of Pharmacy, Second Military Medical University, Shanghai 200433, China;

3. Shanghai Institute of Pharmaceutical Industry, Shanghai 200040, China

Received Date: 2014-10-13

Fund Project: The work was supported by Professor of Chang Jiang Scholars Program, NSFC (No. 81230090), Shanghai Leading Academic Discipline Project (B906), Key laboratory of drug research for special environments, PLA, Shanghai Engineering Research Center for the Preparation of Bioactive Natural Products (No. 10DZ2251300), the Scientific Foundation of Shanghai, China (Nos. 12401900801, 13401900 101), National Major Project of China (No. 2011ZX09307-002-03) and the National Key Technology R&D Program of China (No. 2012BAI29B06)

Abstract: In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of omics technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These omics are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.

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[1]	Kandpal RP, Saviola B, Felton J. The era of'omics unlimited[J]. Biotechniques, 2009, 46(5):351.
[2]	Cavalli-Sforza LL. The human genome diversity project:past, present and future[J]. Nat Rev Genet, 2005, 6(4):333-340.
[3]	Wang L. Pharmacogenomics:a systems approach[J]. Wiley Interdiscip Rev Syst Biol Med, 2010, 2(1):3-22.
[4]	D'Alessandro A and Zolla L. Pharmacoproteomics:a chess game on a protein field[J]. Drug Discov Today, 2010, 15(23-24):1015-1023.
[5]	Beijer HJ, de Blaey CJ. Hospitalisations caused by adverse drug reactions (ADR):a meta-analysis of observational studies[J]. Pharm World Sci, 2002, 24(2):46-54.
[6]	Garnett MJ, Edelman EJ, Heidorn SJ, et al. Systematic identification of genomic markers of drug sensitivity in cancer cells[J]. Nature, 2012, 483(7391):570-575.
[7]	Visscher H, Ross CJ, Rassekh SR, et al. Pharmacogenomic prediction of anthracycline-induced cardiotoxicity in children[J]. J Clin Oncol, 2012, 30(13):1422-1428.
[8]	Qin J, Li R, Raes J, et al. A human gut microbial gene catalogue established by metagenomic sequencing[J]. Nature, 2010, 464(7285):59-65.
[9]	Poinar HN, Schwarz C, Qi J, et al. Metagenomics to paleogenomics:large-scale sequencing of mammoth DNA[J]. Science, 2006, 311(5759):392-394.
[10]	Ley RE, Backhed F, Turnbaugh P, et al. Obesity alters gut microbial ecology[J]. Proc Natl Acad Sci USA, 2005, 102(31):11070-11075.
[11]	Turnbaugh PJ, Ley RE, Mahowald MA, et al. An obesityassociated gut microbiome with increased capacity for energy harvest[J]. Nature, 2006, 444(7122):1027-1031.
[12]	Le Chatelier E, Nielsen T, Qin J, et al. Richness of human gut microbiome correlates with metabolic markers[J]. Nature, 2013, 500(7464):541-546.
[13]	Manichanh C, Rigottier-Gois L, Bonnaud E, et al. Reduced diversity of faecal microbiota in Crohn's disease revealed by a metagenomic approach[J]. Gut, 2006, 55(2):205-211.
[14]	Siggers RH, Siggers J, Boye M, et al. Early administration of probiotics alters bacterial colonization and limits diet-induced gut dysfunction and severity of necrotizing enterocolitis in preterm pigs[J]. J Nutr, 2008, 138(8):1437-1444.
[15]	Scanlan PD, Shanahan F, Clune Y, et al. Culture-independent analysis of the gut microbiota in colorectal cancer and polyposis[J]. Environ Microbiol, 2008, 10(3):789-798.
[16]	Larsen N, Vogensen FK, van den Berg FW, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults[J]. PLoS One, 2010, 5(2):e9085.
[17]	Laird PW. Principles and challenges of genome-wide DNA methylation analysis[J]. Nat Rev Genet, 2010, 11(3):191-203.
[18]	Jenuwein T, Allis CD. Translating the histone code[J]. Science, 2001, 293(5532):1074-1080.
[19]	Hake SB, Allis CD. Histone H3 variants and their potential role in indexing mammalian genomes:the H3 barcode hypothesis [J]. Proc Natl Acad Sci USA, 2006, 103(17):6428-6435.
[20]	Grewal SI, Elgin SC. Transcription and RNA interference in the formation of heterochromatin[J]. Nature, 2007, 447(7143):399-406.
[21]	Fraser P, Bickmore W. Nuclear organization of the genome and the potential for gene regulation[J]. Nature, 2007, 447(7143):413-417.
[22]	Sandoval J, Esteller M. Cancer epigenomics:beyond genomics[J]. Curr Opin Genet Dev, 2012, 22(1):50-55.
[23]	Bradbury J. Human epigenome project-up and running[J]. PLoS Biol, 2003, 1(3):e82.
[24]	Kulis M, Esteller M. DNA methylation and cancer[J]. Adv Genet, 2010, 70:27-56.
[25]	Strahl BD, Allis CD. The language of covalent histone modifications[J]. Nature, 2000, 403(6765):41-45.
[26]	Maskos U, Southern EM. Oligonucleotide hybridizations on glass supports:a novel linker for oligonucleotide synthesis and hybridization properties of oligonucleotides synthesised in situ[J]. Nucleic Acids Res, 1992, 20(7):1679-1684.
[27]	Velculescu VE, Zhang L, Vogelstein B, et al. Serial analysis of gene expression[J]. Science, 1995, 270(5235):484-487.
[28]	Brenner S, Johnson M, Bridgham J, et al. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays[J]. Nat Biotechnol, 2000, 18(6):630-634.
[29]	Morin R, Bainbridge M, Fejes A, et al. Profiling the HeLa S3 transcriptome using randomly primed cDNA and massively parallel short-read sequencing[J]. Biotechniques, 2008, 45(1):81-94.
[30]	Chu Y, Corey DR. RNA sequencing:platform selection, experimental design, and data interpretation[J]. Nucleic Acid Ther, 2012, 22(4):271-274.
[31]	Wang Z, Gerstein M, Snyder M. RNA-Seq:a revolutionary tool for transcriptomics[J]. Nat Rev Genet, 2009, 10(1):57-63.
[32]	Sutherland GT, Janitz M, Kril JJ. Understanding the pathogenesis of Alzheimer's disease:will RNA-Seq realize the promise of transcriptomics?[J]. J Neurochem, 2011, 116(6):937-946.
[33]	Fehlbaum-Beurdeley P, Sol O, Desire L, et al. Validation of AclarusDx, a blood-based transcriptomic signature for the diagnosis of Alzheimer's disease[J]. J Alzheimers Dis, 2012, 32(1):169-181.
[34]	Voineagu I, Wang X, Johnston P, et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology[J]. Nature, 2011, 474(7351):380-384.
[35]	Heidecker B, Hare JM. The use of transcriptomic biomarkers for personalized medicine[J]. Heart Fail Rev, 2007, 12(1):1-11.
[36]	Cui Y, Paules RS. Use of transcriptomics in understanding mechanisms of drug-induced toxicity[J]. Pharmacogenomics, 2010, 11(4):573-585.
[37]	Kandoth C, Schultz N, Cherniack AD, et al. Integrated genomic characterization of endometrial carcinoma[J]. Nature, 2013, 497(7447):67-73.
[38]	Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups[J]. Nature, 2012, 486(7403):346-352.
[39]	Labb RM, Irimia M, Currie KW, et al. A comparative transcriptomic analysis reveals conserved features of stem cell pluripotency in planarians and mammals[J]. Stem Cells, 2012, 30(8):1734-1745.
[40]	Wilkins MR, Pasquali C, Appel RD, et al. From proteins to proteomes:large scale protein identification by two-dimensional electrophoresis and amino acid analysis[J]. Biotechnology, 1996, 14(1):61-65.
[41]	Anderson NL, Anderson NG. Proteome and proteomics:New technologies, new concepts, and new words[J]. Electrophoresis, 1998, 19(11):1853-1861.
[42]	Blackstock WP, Weir MP. Proteomics:quantitative and physical mapping of cellular proteins[J]. Trends Biotechnol, 1999, 17(3):121-127.
[43]	Marouga R, David S, Hawkins E. The development of the DIGE system:2D fluorescence difference gel analysis technology[J]. Anal Bioanal Chem, 2005, 382(3):669-678.
[44]	Tannu NS, Hemby SE. Two-dimensional fluorescence difference gel electrophoresis for comparative proteomics profiling[J]. Nat Protoc, 2006, 1(4):1732-1742.
[45]	Bennett KL, Funk M, Tschernutter M, et al. Proteomic analysis of human cataract aqueous humour:Comparison of one-dimensional gel LCMS with two-dimensional LCMS of unlabelled and iTRAQ(R)-labelled specimens[J]. J Proteomics, 2011, 74(2):151-166.
[46]	Irar S, Brini F, Masmoudi K, et al. Combination of 2DE and LC for plant proteomics analysis[J]. Methods Mol Biol, 2014, 1072:131-140.
[47]	Stalmach A, Albalat A, Mullen W, et al. Recent advances in capillary electrophoresis coupled to mass spectrometry for clinical proteomic applications[J]. Electrophoresis, 2013, 34(11):1452-1464.
[48]	Asara J, Christofk H, Freimark L, et al. A label-free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen[J]. Proteomics, 2008, 8(5):994-999.
[49]	Gygi SP, Rist B, Gerber SA, et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags[J]. Nat Biotechnol, 1999, 17(10):994-999.
[50]	Zieske LR. A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies[J]. J Exp Bot, 2006, 57(7):1501-1508.
[51]	Schwanhusser B, Gossen M, Dittmar G, et al. Global analysis of cellular protein translation by pulsed SILAC[J]. Proteomics, 2009, 9(1):205-209.
[52]	Chen J, Khne T, Rcken C, et al. Proteome analysis of gastric cancer metastasis by two-dimensional gel electrophoresis and matrix assisted laser desorption/ionization-mass spectrometry for identification of metastasis-related proteins[J]. J Proteome Res, 2004, 3(5):1009-1016.
[53]	Ping S, Wang S, Zhang J, et al. Effect of all-trans-retinoic acid on mRNA binding protein p62 in human gastric cancer cells[J]. Int J Biochem Cell Biol, 2005, 37(3):616-627.
[54]	Poon TC, Sung JJ, Chow SM, et al. Diagnosis of gastric cancer by serum proteomic fingerprinting[J]. Gastroenterology, 2006, 130(6):1858-1864.
[55]	Mu AK, Chan YS, Kang SS, et al. Detection of host-specific immunogenic proteins in the saliva of patients with oral squamous cell carcinoma[J]. J Immunoassay Immunochem, 2014, 35(2):183-193.
[56]	Kubota D, Yoshida A, Kikuta K, et al. Proteomic approach to gastrointestinal stromal tumor identified prognostic biomarkers[J]. J Proteomics Bioinform, 2014, 7(1):10-16.
[57]	Lim YP. Mining the tumor phosphoproteome for cancer markers[J]. Clin Cancer Res, 2005, 11(9):3163-3169.
[58]	Yu LR, Issaq HJ, Veenstra TD. Phosphoproteomics for the discovery of kinases as cancer biomarkers and drug targets[J]. Proteomics Clin Appl, 2007, 1(9):1042-1057.
[59]	Bolger SJ, Hurtado PA, Hoffert JD, et al. Quantitative phosphoproteomics in nuclei of vasopressin-sensitive renal collecting duct cells[J]. Am J Physiol Cell Physiol, 2012, 303(10):1006-1020.
[60]	Rinschen MM, Yu MJ, Wang G, et al. Quantitative phosphoproteomic analysis reveals vasopressin V2-receptor-dependent signaling pathways in renal collecting duct cells[J]. Proc Natl Acad Sci USA, 2010, 107(8):3882-3887.
[61]	Zhao B, Knepper MA, Chou CL, et al. Large-scale phosphotyrosine proteomic profiling of rat renal collecting duct epithelium reveals predominance of proteins involved in cell polarity determination[J]. Am J Physiol Cell Physiol, 2012, 302(1):27-45.
[62]	Feric M, Zhao B, Hoffert JD, et al. Large-scale phosphoproteomic analysis of membrane proteins in renal proximal and distal tubule[J]. Am J Physiol Cell Physiol, 2011, 300(4):755-770.
[63]	Gonzales PA, Pisitkun T, Hoffert JD, et al. Large-scale proteomics and phosphoproteomics of urinary exosomes[J]. J Am Soc Nephrol, 2009, 20(2):363-379.
[64]	Hoffert JD, Pisitkun T, Wang G, et al. Quantitative phosphoproteomics of vasopressin-sensitive renal cells:regulation of aquaporin-2 phosphorylation at two sites[J]. Proc Natl Acad Sci USA, 2006, 103(18):7159-7164.
[65]	Tissot B, North SJ, Ceroni A, et al. Glycoproteomics:past, present and future[J]. FEBS Lett, 2009, 583(11):1728-1735.
[66]	Hagglund P, Bunkenborg J, Elortza F, et al. A new strategy for identification of N-glycosylated proteins and unambiguous assignment of their glycosylation sites using HILIC enrichment and partial deglycosylation[J]. J Proteome Res, 2004, 3(3):556-566.
[67]	Yang Z, Hancock WS. Approach to the comprehensive analysis of glycoproteins isolated from human serum using a multi-lectin affinity column[J]. J Chromatogr A, 2004, 1053(1-2):79-88.
[68]	Hirabayashi J, Hayama K, Kaji H, et al. Affinity capturing and gene assignment of soluble glycoproteins produced by the nematode Caenorhabditis elegans[J]. J Biochem, 2002, 132(1):103-114.
[69]	Madera M, Mechref Y, Klouckova I, et al. Semiautomated high-sensitivity profiling of human blood serum glycoproteins through lectin preconcentration and multidimensional chromatography/tandem mass spectrometry[J]. J Proteome Res, 2006, 5(9):2348-2363.
[70]	Kameyama A, Kikuchi N, Nakaya S, et al. A strategy for identification of oligosaccharide structures using observational multistage mass spectral library[J]. Anal Chem, 2005, 77(15):4719-4725.
[71]	Yen TY, Haste N, Timpe LC, et al. Using a cell line breast cancer progression system to identify biomarker candidates[J]. J Proteomics, 2014, 96:173-183.
[72]	Ahn JM, Sung HJ, Yoon YH, et al. Integrated glycoproteomics demonstrates fucosylated serum paraoxonase 1 alterations in small cell lung cancer[J]. Mol Cell Proteomics, 2014, 13(1):30-48.
[73]	Bones J, Byrne JC, O'Donoghue N, et al. Glycomic and glycoproteomic analysis of serum from patients with stomach cancer reveals potential markers arising from host defense response mechanisms[J]. J Proteome Res, 2011, 10(3):1246-1265.
[74]	Wu J, Xie X, Liu Y, et al. Identification and confirmation of differentially expressed fucosylated glycoproteins in the serum of ovarian cancer patients using a lectin array and LC-MS/MS[J]. J Proteome Res, 2012, 11(9):4541-4552.
[75]	Ito K, Kuno A, Ikehara Y, et al. LecT-Hepa, a glyco-marker derived from multiple lectins, as a predictor of liver fibrosis in chronic hepatitis C patients[J]. Hepatology, 2012, 56(4):1448-1456.
[76]	Butterfield DA, Owen JB. Lectin-affinity chromatography brain glycoproteomics and Alzheimer disease:insights into protein alterations consistent with the pathology and progression of this dementing disorder[J]. Proteomics Clin Appl, 2011, 5(1-2):50-56.
[77]	Strassberger V, Fugmann T, Neri D, et al. Chemical proteomic and bioinformatic strategies for the identification and quantification of vascular antigens in cancer[J]. J Proteomics, 2010, 73(10):1954-1973.
[78]	Adam GC, Sorensen EJ, Cravatt BF. Chemical strategies for functional proteomics[J]. Mol Cell Proteomics, 2002, 1(10):781-790.
[79]	Terstappen GC, Schlupen C, Raggiaschi R, et al. Target deconvolution strategies in drug discovery[J]. Nat Rev Drug Discov, 2007, 6(11):891-903.
[80]	Lomenick B, Olsen RW, Huang J. Identification of direct protein targets of small molecules[J]. ACS ChemBiol, 2010, 6(1):34-46.
[81]	Sato S-i, Murata A, Shirakawa T, et al. Biochemical target isolation for novices:affinity-based strategies[J]. Chem Biol, 2010, 17(6):616-623.
[82]	Lomenick B, Hao R, Jonai N, et al. Target identification using drug affinity responsive target stability (DARTS)[J]. Proc Natl Acad Sci USA, 2009, 106(51):21984-21989.
[83]	Huang J, Zhu H, Haggarty SJ, et al. Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips[J]. Proc Natl Acad Sci USA, 2004, 101(47):16594-16599.
[84]	Barabasi A-L, Oltvai ZN. Network biology:understanding the cell's functional organization[J]. Nat Rev Genet, 2004, 5(2):101-113.
[85]	Greenbaum DC, Baruch A, Grainger M, et al. A role for the protease falcipain 1 in host cell invasion by the human malaria parasite[J]. Science, 2002, 298(5600):2002-2006.
[86]	Zhang XW, Yan XJ, Zhou ZR, et al. Arsenic trioxide controls the fate of the PML-RARalpha oncoprotein by directly binding PML[J]. Science, 2010, 328(5975):240-243.
[87]	Nicholson JK. Global systems biology, personalized medicine and molecular epidemiology[J]. Mol Syst Biol, 2006, 2:52
[88]	Trygg J, Holmes E, Lundstedt T. Chemometrics in metabonomics[J]. J Proteome Res, 2007, 6(2):469-479.
[89]	Smith CA, Want EJ, O'Maille G, et al. XCMS:Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification[J]. Anal Chem, 2006, 78(3):779-787.
[90]	Tautenhahn R, Patti GJ, Rinehart D, et al. XCMS Online:a web-based platform to process untargeted metabolomic data[J]. Anal Chem, 2012, 84(11):5035-5039.
[91]	Katajamaa M, Miettinen J, Oreič M. MZmine:toolbox for processing and visualization of mass spectrometry based molecular profile data[J]. Bioinformatics, 2006, 22(5):634-636.
[92]	Lommen A. MetAlign:interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing[J]. Anal Chem, 2009, 81(8):3079-3086.
[93]	Baran R, Kochi H, Saito N, et al. MathDAMP:a package for differential analysis of metabolite profiles[J]. BMC Bioinformatics, 2006, 7:530.
[94]	Robertson DG. Metabonomics in toxicology:a review[J]. Toxicol Sci, 2005, 85(2):809-822.
[95]	Sabatine MS, Liu E, Morrow DA, et al. Metabolomic identification of novel biomarkers of myocardial ischemia[J]. Circulation, 2005, 112(25):3868-3875.
[96]	Zhang A, Sun H, Yan G, et al. Metabolomics in diagnosis and biomarker discovery of colorectal cancer[J]. Cancer Lett, 2014, 345(1):17-20.
[97]	Denkert C, Budczies J, Weichert W, et al. Metabolite profiling of human colon carcinoma--deregulation of TCA cycle and amino acid turnover[J]. Mol Cancer, 2008, 7(72):1476-4598.
[98]	Clayton TA, Lindon JC, Cloarec O, et al. Pharmaco-metabonomic phenotyping and personalized drug treatment[J]. Nature, 2006, 440(7087):1073-1077.
[99]	Wang X, Yan SK, Dai WX, et al. A metabonomic approach to chemosensitivity prediction of cisplatin plus 5-fluorouracil in a human xenograft model of gastric cancer[J]. Int J Cancer, 2010, 127(12):2841-2850.
[100]	Amacher DE. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity[J]. Toxicol Appl Pharmacol, 2010, 245(1):134-142.
[101]	Klawitter J, Haschke M, Kahle C, et al. Toxicodynamic effects of ciclosporin are reflected by metabolite profiles in the urine of healthy individuals after a single dose[J]. Br J Clin Pharmacol, 2010, 70(2):241-251.
[102]	Ichikawa W. Prediction of clinical outcome of fluoropyrimidine-based chemotherapy for gastric cancer patients, in terms of the 5-fluorouracil metabolic pathway[J]. Gastric Cancer, 2006, 9(3):145-155.
[103]	Howells DW, Sena ES, O'Collins V, et al. Improving the efficiency of the development of drugs for stroke[J]. Int J Stroke, 2012, 7(5):371-377.
[104]	Han X, Gross RW. Global analyses of cellular lipidomes directly from crude extracts of biological samples by ESI mass spectrometry:a bridge to lipidomics[J]. J Lipid Res, 2003, 44(6):1071-1079.
[105]	Wenk MR. The emerging field of lipidomics[J]. Nat Rev Drug Discov, 2005, 4(7):594-610.
[106]	Watson AD. Thematic review series:systems biology approaches to metabolic and cardiovascular disorders. Lipidomics:a global approach to lipid analysis in biological systems[J]. J Lipid Res, 2006, 47(10):2101-2111.
[107]	Bligh EG, Dyer WJ. A rapid method of total lipid extraction and purification[J]. Can J Biochem Physiol, 1959, 37(8):911-917.
[108]	Wenk MR. Lipidomics in drug and biomarker development[J]. Expert Opin Drug Discov, 2006, 1(7):723-736.
[109]	Marechal E, Riou M, Kerboeuf D, et al. Membrane lipidomics for the discovery of new antiparasitic drug targets[J]. Trends Parasitol, 2011, 27(11):496-504.
[110]	Adibhatla RM, Hatcher JF and Dempsey RJ. Lipids and lipidomics in brain injury and diseases[J]. Aaps J, 2006, 8(2):E314-321.
[111]	Bilder RM, Sabb FW, Cannon TD, et al. Phenomics:the systematic study of phenotypes on a genome-wide scale[J]. Neuroscience, 2009, 164(1):30-42.
[112]	Joy T, Hegele RA. Genetics of metabolic syndrome:is there a role for phenomics?[J]. Curr Atheroscler Rep, 2008, 10(3):201-208.
[113]	Finkel E. With 'Phenomics', plant scientists hope to shift breeding into overdrive[J]. Science, 2009, 325(5939):380-381.
[114]	Pizza M, Scarlato V, Masignani V, et al. Identification of vaccine candidates against serogroup B meningococcus by whole-genome sequencing[J]. Science, 2000, 287(5459):1816-1820.
[115]	Bambini S, Rappuoli R. The use of genomics in microbial vaccine development[J]. Drug Discov Today, 2009, 14(5-6):252-260.
[116]	He Y. Omics-based systems vaccinology for vaccine target identification[J]. Drug Develop Res, 2012, 73(8):559-568.
[117]	Bulman A, Neagu M, Constantin C. Immunomics in skin cancer-improvement in diagnosis, Prognosis and Therapy Monitoring[J]. Curr Proteomics, 2013, 10(3):202.
[118]	Haraguchi H. Metallomics as integrated biometal science[J]. J Anal At Spectrom, 2004, 19(1):5-14.
[119]	Szpunar J. Advances in analytical methodology for bioinorganic speciation analysis:metallomics, metalloproteomics and heteroatom-tagged proteomics and metabolomics[J]. Analyst, 2005, 130(4):442-465.
[120]	Chry CC, Gnther D, Cornelis R, et al. Detection of metals in proteins by means of polyacrylamide gel electrophoresis and laser ablation-inductively coupled plasma-mass spectrometry:Application to selenium[J]. Electrophoresis, 2003, 24(19-20):3305-3313.
[121]	Carmona A, Cloetens P, Devs G, et al. Nano-imaging of trace metals by synchrotron X-ray fluorescence into dopaminergic single cells and neurite-like processes[J]. J Anal At Spectrom, 2008, 23(8):1083-1088.
[122]	Gonzlez-Fernndez M, Garca-Barrera T, Arias-Borrego A, et al. Metallomics integrated with proteomics in deciphering metal-related environmental issues[J]. Biochimie, 2009, 91(10):1311-1317.
[123]	Sun X, Tsang C-N, Sun H. Identification and characterization of metallodrug binding proteins by (metallo) proteomics[J]. Metallomics, 2009, 1(1):25-31.
[124]	Yan XD, Pan LY, Yuan Y, et al. Identification of platinumresistance associated proteins through proteomic analysis of human ovarian cancer cells and their platinum-resistant sublines[J]. J Proteome Res, 2007, 6(2):772-780.
[125]	Schooley K, Zhu P, Dower SK, et al. Regulation of nuclear translocation of nuclear factor-kappaB relA:evidence for complex dynamics at the single-cell level[J]. Biochem J, 2003, 369(Pt 2):331-339.
[126]	Valet G. Cytomics as a new potential for drug discovery[J]. Drug Discov Today, 2006, 11(17):785-791.
[127]	Jang YJ, Jeon OH, Kim DS. Saxatilin, a snake venom disintegrin, regulates platelet activation associated with human vascular endothelial cell migration and invasion[J]. J Vasc Res, 2007, 44(2):129-137.
[128]	Shanks RH, Rizzieri DA, Flowers JL, et al. Preclinical evaluation of gemcitabine combination regimens for application in acute myeloid leukemia[J]. Clin Cancer Res, 2005, 11(11):4225-4233.
[129]	Danku JM, Gumaelius L, Baxter I, et al. A high-throughput method for Saccharomyces cerevisiae (yeast) ionomics[J]. J Anal At Spectrom, 2009, 24(1):103-107.
[130]	Young LW, Westcott ND, Attenkofer K, et al. A high-throughput determination of metal concentrations in whole intact Arabidopsis thaliana seeds using synchrotron-based X-ray fluorescence spectroscopy[J]. J Synchrotron Radiat, 2006, 13(4):304-313.
[131]	Eide DJ, Clark S, Nair TM, et al. Characterization of the yeast ionome:a genome-wide analysis of nutrient mineral and trace element homeostasis in Saccharomyces cerevisiae[J]. Genome Biol, 2005, 6(9):R77.
[132]	Ziegler G, Terauchi A, Becker A, et al. Ionomic screening of field-grown soybean identifies mutants with altered seed elemental composition[J]. The Plant Genome, 2013, 6(2):1-9.
[133]	Sanchez C, Lachaize C, Janody F, et al. Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an internet database[J]. Nucleic Acids Res, 1999, 27(1):89-94.
[134]	Sakurai T, Amemiya A, Ishii M, et al. Orexins and orexin receptors:a family of hypothalamic neuropeptides and G protein-coupled receptors that regulate feeding behavior[J]. Cell, 1998, 92(4):573-585.
[135]	Maglott D, Ostell J, Pruitt KD, et al. Entrez Gene:genecentered information at NCBI[J]. Nucleic Acids Res, 2007, 35(S1):D26-D31.
[136]	Rhodes DR, Kalyana-Sundaram S, Mahavisno V, et al. Oncomine 3.0:genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles[J]. Neoplasia, 2007, 9(2):166-180.
[137]	Gao Z, Li H, Zhang H, et al. PDTD:a web-accessible protein database for drug target identification[J]. BMC Bioinformatics, 2008, 9(104):1471-2105.
[138]	Jayapal M, Melendez AJ. DNA microarray technology for target identification and validation[J]. Clin Exp Pharm Physiol, 2006, 33(5-6):496-503.
[139]	Ricciarelli R, d'Abramo C, Massone S, et al. Microarray analysis in Alzheimer's disease and normal aging[J]. IUBMB life, 2004, 56(6):349-354.
[140]	Grnblatt E, Mandel S, Maor G, et al. Gene expression analysis in N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mice model of Parkinson's disease using cDNA microarray:effect of Rapomorphine[J].J Neurochem, 2001, 78(1):1-12.
[141]	Stam RW, den Boer ML, Meijerink JP, et al. Differential mRNA expression of Ara-C-metabolizing enzymes explains Ara-C sensitivity in MLL gene-rearranged infant acute lymphoblastic leukemia[J]. Blood, 2003, 101(4):1270-1276.
[142]	Fong D, Spizzo G, Gostner JM, et al. TROP2:a novel prognostic marker in squamous cell carcinoma of the oral cavity[J]. Mod Pathol, 2007, 21(2):186-191.
[143]	Keskin O, Gursoy A, Ma B, et al. Towards drugs targeting multiple proteins in a systems biology approach[J]. Curr Top Med Chem, 2007, 7(10):943-951.
[144]	Gresham V, McLeod HL. Genomics:Applications in mechanism elucidation[J]. Adv Drug Deliv Rev, 2009, 61(5):369-374.
[145]	Attia SM, Ahmad SF, Zoheir KM, et al. Genotoxic evaluation of chloroacetonitrile in murine marrow cells and effects on DNA damage repair gene expressions[J]. Mutagenesis, 2014, 29(1):55-62.
[146]	Wetmore BA, Merrick BA. Toxicoproteomics:proteomics applied to toxicology and pathology[J]. Toxicol Pathol, 2004, 32(6):619-642.
[147]	Gresham V, McLeod HL. Genomics:applications in mechanism elucidation[J]. Adv Drug Deliv Rev, 2009, 61(5):369-374.
[148]	Bouhifd M, Hartung T, Hogberg HT, et al. Review:toxicometabolomics[J]. J Appl Toxicol, 2013, 33(12):1365-1383.
[149]	Nicholson JK, Everett JR, Lindon JC. Longitudinal pharmacometabonomics for predicting patient responses to therapy:drug metabolism, toxicity and efficacy[J]. Expert Opin Drug Metab Toxicol, 2012, 8(2):135-139.
[150]	Soga T, Baran R, Suematsu M, et al. Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption[J]. J Bio Chem, 2006, 281(24):16768-16776.
[151]	Giacomini KM, Krauss RM, Roden DM, et al. When good drugs go bad[J]. Nature, 2007, 446(7139):975-977.
[152]	Loscalzo J, Kohane I, Barabasi AL. Human disease classification in the postgenomic era:a complex systems approach to human pathobiology[J]. Mol Syst Biol, 2007, 3(124):10.
[153]	Johnson JA. Advancing management of hypertension through pharmacogenomics[J]. Ann Med, 2012, 44(S1):S17-S22.
[154]	Gupta S and Awasthi S. Pharmacogenomics of pediatric asthma[J]. Indian J Hum Genet, 2010, 16(3):111-118.
[155]	Aslibekyan S, Straka RJ, Irvin MR, et al. Pharmacogenomics of high-density lipoprotein-cholesterol-raising therapies[J]. Expert Rev Cardiovasc Ther, 2013, 11(3):355-364.
[156]	Ingle JN. Pharmacogenomics of endocrine therapy in breast cancer[J]. J Hum Genet, 2013, 58(6):306-312.
[157]	Lee W, Lockhart AC, Kim RB, et al. Cancer pharmacogenomics:powerful tools in cancer chemotherapy and drug development[J]. The Oncologist, 2005, 10(2):104-111.
[158]	Ferrari P. Pharmacogenomics:a new approach to individual therapy of hypertension?[J]. Curr Opin Nephrol Hypertens, 1998, 7(2):217-222.
[159]	Hancox RJ, Sears MR, Taylor DR. Polymorphism of the beta2-adrenoceptor and the response to long-term beta2-agonist therapy in asthma[J]. Eur Respir J, 1998, 11(3):589-593.
[160]	Holmes E, Nicholson JK, Tranter G. Metabonomic characterization of genetic variations in toxicological and metabolic responses using probabilistic neural networks[J]. Chem Res Toxicol, 2001, 14(2):182-191.
[161]	Nicholson JK, Wilson ID, Lindon JC. Pharmacometabonomics as an effector for personalized medicine[J]. Pharmacogenomics, 2011, 12(1):103-111.
[162]	van Wietmarschen HA, der Greef Jv, Schron Y, et al. Evaluation of symptom, clinical chemistry and metabolomics profiles during Rehmannia six formula (R6) treatment:An integrated and personalized data analysis approach[J]. J Ethnopharmacol, 2013, 150(3):851-859.
[163]	Keun HC, Sidhu J, Pchejetski D, et al. Serum molecular signatures of weight change during early breast cancer chemotherapy[J]. Clin Canc Res, 2009, 15(21):6716-6723.
[164]	Klayman DL. Qinghaosu (artemisinin):an antimalarial drug from China[J]. Science, 1985, 228(4703):1049-1055.
[165]	Chen GQ, Shi XG, Tang W, et al. Use of arsenic trioxide (As2O3) in the treatment of acute promyelocytic leukemia (APL):I. As2O3 exerts dose-dependent dual effects on APL cells[J]. Blood, 1997, 89(9):3345-3353.
[166]	Ma WH, Lu Y, Huang H, et al. Schisanwilsonins A-G and related anti-HBV lignans from the fruits of Schisandra wilsoniana[J]. Bioorg Med Chem Lett, 2009, 19(17):4958-4962.
[167]	Ma X, Gang DR. In vitro production of huperzine A, a promising drug candidate for Alzheimer's disease[J]. Phytochemistry, 2008, 69(10):2022-2028.
[168]	Qiu J. Traditional medicine:a culture in the balance[J]. Nature, 2007, 448(7150):126-128.
[169]	Zhang YB, Wang J, Wang ZT, et al. DNA microarray for identification of the herb of Dendrobium species from Chinese medicinal formulations[J]. Planta Med, 2003, 69(12):1172-1174.
[170]	Wang GL, Chen CB, Gao JM, et al. Investigation on the molecular mechanisms of anti-hepatocarcinoma herbs of traditional Chinese medicine by cell cycle microarray[J]. China J Chin Mater Med, 2005, 30(1):50-54.
[171]	Zhang ZJ, Li P, Wang Z, et al. A comparative study on the individual and combined effects of baicalin and jasminoidin on focal cerebral ischemia-reperfusion injury[J]. Brain Res, 2006, 1123(1):188-195.
[172]	Hara A, Iizuka N, Hamamoto Y, et al. Molecular dissection of a medicinal herb with anti-tumor activity by oligonucleotide microarray[J]. Life Sci, 2005, 77(9):991-1002.
[173]	Yue QX, Cao ZW, Guan SH, et al. Proteomics characterization of the cytotoxicity mechanism of ganoderic acid D and computer-automated estimation of the possible drug target network[J]. Mol Cell Proteomics, 2008, 7(5):949-961.
[174]	Yue QX, Song XY, Ma C, et al. Effects of triterpenes from Ganoderma lucidum on protein expression profile of HeLa cells[J]. Phytomedicine, 2010, 17(8-9):606-613.
[175]	Wang X, Chen Y, Han QB, et al. Proteomic identification of molecular targets of gambogic acid:role of stathmin in hepatocellular carcinoma[J]. Proteomics, 2009, 9(2):242-253.
[176]	Chen M, Su M, Zhao L, et al. Metabonomic study of aristolochic acid-induced nephrotoxicity in rats[J]. J Proteome Res, 2006, 5(4):995-1002.
[177]	Li WX, Tang YP, Guo JM, et al. Comparative metabolomics analysis on hematopoietic functions ofherb pair Gui-Xiong by ultra-high-performance liquidchromatography coupled to quadrupole time-of-flight massspectrometry and pattern recognition approach[J]. J Chromatogr A, 2014, 1346:49-56.
[178]	Li L, Wang J, Ren J, et al. Metabonomics analysis of the urine of rats with Qi deficiency and blood stasis syndrome based on NMR techniques[J]. Chin Sci Bull, 2007, 52(22):3068-3073.
[179]	Wang X, Zhang A, Han Y, et al. Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease[J]. Mol Cell Proteomics, 2012, 11(8):370-380.
[180]	Droste P, Miebach S, Niedenfhr S, et al. Visualizing multi-omics data in metabolic networks with the software Omix-a case study[J]. Biosystems, 2011, 105(2):154-161.
[181]	Haoudi A, Bensmail H. Bioinformatics and data mining in proteomics[J]. Expert Rev Proteomics, 2006, 3(3):333-343.
[182]	Wolstencroft K, Haines R, Fellows D, et al. The Taverna workflow suite:designing and executing workflows of Web Services on the desktop, web or in the cloud[J]. Nucleic Acids Res, 2013, 41(Web Server issue):W557-561.
[183]	McIntyre RS, Cha DS, Jerrell JM, et al. Advancing biomarker research:utilizing 'Big Data' approaches for the characterization and prevention of bipolar disorder[J]. BipolarDisord, 2014, 16(5):531-547.
[184]	Hassani S, Martens H, Qannari EM, et al. Analysis of-omics data:Graphical interpretation- and validation tools in multiblock methods[J]. Chemometr Intell Lab Syst, 2010, 104(1):140-153.
[185]	Zhang Z, Chen J, Guo F, et al. A high-temporal resolution technology for dynamic proteomic analysis based on 35S labeling[J]. PLoS One, 2008, 3(8):e2991.
[186]	Chen R, Mias GI, Li-Pook-Than J, et al. Personal omics profiling reveals dynamic molecular and medical phenotypes[J]. Cell, 2012, 148(6):1293-1307.
[187]	Nakanishi Y, Fukuda S, Chikayama E, et al. Dynamic omics approach identifies nutrition-mediated microbial interactions[J]. J Proteome Res, 2010, 10(2):824-836.

“Omics” in pharmaceutical research:overview, applications, challenges, and future perspectives

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通讯作者: 陈斌, bchen63@163.com

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