Bioinformatics and Omics

  • Timothy Craig Allen
  • Philip T. Cagle
Part of the Molecular Pathology Library book series (MPLB, volume 2)


Bioinformatics has become an essential part of omics research and requires unique practical and analytical skills for appropriate results interpretation. Bioinformatics uses computers and statistics to perform extensive omics-related research by searching biological databases and comparing gene sequences and protein on a vast scale to identify sequences or proteins that differ between diseased and healthy tissues, or between different phenotypes of the same disease.30, 31, 32, 33, 34, 35, 36, 37 The techniques used in omics are called high throughput because they involve analysis of very large numbers of genes, gene expression, or proteins in one procedure or combination of procedures. The vast amounts of data generated by these high-throughput studies typically require computers for analysis and comparison of differences between diseased and physiological cells and tissues, a key feature of bioinformatics. Omics and bioinformatics are used not only for the study of the genes and signaling pathways involved in human diseases, but also for identifying potential targets of therapy and the design of therapeutic drugs.

Omics – a suffix signifying the measurement of the entire complement of a given level of biological molecules and information – today encompasses a variety of new technologies that can help explain normal and abnormal cell pathways, networks, and processes via the simultaneous monitoring of thousands of molecular components.6,7


Suppression Subtractive Hybridization Omics Technology Single Nucleotide Polymorphism Detection Human Mitochondrial Genome International Human Genome Sequencing Consortium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Biron DG, Brun C, Lefevre T, et al. The pitfalls of proteonomics experiments without the correct use of bioinformatics tools. Proteomics. 2006;20:5577–5596.CrossRefGoogle Scholar
  2. 2.
    McKusick VA. Genomics: structure and functional studies of genomes. Genomics. 1997;45:244–249.PubMedCrossRefGoogle Scholar
  3. 3.
    Palagi PM, Hernandez P, Walther D, Appel RD. Proteome informatics I: bioinformatics tools for processing experimental data. Proteomics. 2006;6:5435–5444.PubMedCrossRefGoogle Scholar
  4. 4.
    Lisacek F, Cohen-Boulakia S, Appel RD. Proteome informatics II: bioinformatics for comparative proteomics. Proteomics. 2006;6: 5445–5466.PubMedCrossRefGoogle Scholar
  5. 5.
    Maojo V, Martin-Sanchez F. Bioinformatics: towards new directions for public health. Methods Inf Med. 2004;43:208–214.PubMedGoogle Scholar
  6. 6.
    Bilello JA. The agony and ecstasy of “OMIC” technologies in drug development. Curr Mol Med. 2005;5:39–52.PubMedCrossRefGoogle Scholar
  7. 7.
    Morel NM, Holland JM, van der Greef P, et al. Primer on medial genomics, part. XIV Introduction to systems biology: a new approach to understanding disease and treatment. Mayo Clin Proc. 2004;79:651–658.PubMedCrossRefGoogle Scholar
  8. 8.
    Provart NJ, McCourt P. Systems approaches to understanding cell signaling and gene regulation. Curr Opin Plant Biol. 2004;7:605–609.PubMedCrossRefGoogle Scholar
  9. 9.
    Wheelock AM, Goto S. Effects of post-electrophoretic analysis on variance in gel-based proteomics. Expert Rev Proteomics. 2006;3:129–142.PubMedCrossRefGoogle Scholar
  10. 10.
    Debouck C, Metcalf B. The impact of genomics on drug discovery. Annu Rev Pharmacol Toxicol. 2000;40:193–207.PubMedCrossRefGoogle Scholar
  11. 11.
    Ghosh D. High throughput and global approaches to gene expression. Comb Chem High Throughput Screen. 2000;3:411–420.PubMedGoogle Scholar
  12. 12.
    Hanke J. Genomics and new technologies as catalysts for change in the drug discovery paradigm. J Law Med Ethics. 2000;28(4 suppl):15–22.PubMedGoogle Scholar
  13. 13.
    Harris T. Genetics, genomics, and drug discovery. Med Res Rev. 2000;20:203–211.PubMedCrossRefGoogle Scholar
  14. 14.
    Rudert F. Genomics and proteomics tools for the clinic. Curr Opin Mol Ther. 2000;2:633–642.PubMedGoogle Scholar
  15. 15.
    Merrick BA, Bruno ME. Genomic and proteomic profiling for biomarkers and signature profiles of toxicity. Curr Opin Mol Ther. 2004;6:600–667.PubMedGoogle Scholar
  16. 16.
    Chalkley RJ, Hansen KC, Baldwin MA. Bioinformatic methods to exploit mass spectrometric data for proteomic applications. Methods Enzymol. 2005;402:289–312.PubMedCrossRefGoogle Scholar
  17. 17.
    Dennis JL, Oien KA. Hunting the primary: novel strategies for defining the origin of tumours. J Pathol. 2005;205:236–247.PubMedCrossRefGoogle Scholar
  18. 18.
    Englbrecht CC, Facius A. Bioinformatics challenges in proteomics. Comb Chem High Throughput Screen. 2005;8:705–715.PubMedCrossRefGoogle Scholar
  19. 19.
    Fung ET, Weinberger SR, Gavin E, Zhang F. Bioinformatics approaches in clinical proteomics. Expert Rev Proteomics. 2005;2:847–862.PubMedCrossRefGoogle Scholar
  20. 20.
    Kremer A, Schneider R, Terstappen GC. A bioinformatics perspective on proteomics: data storage, analysis, and integration. Biosci Rep. 2005;25:95–106.PubMedCrossRefGoogle Scholar
  21. 21.
    Mount DW, Pandey R. Using bioinformatics and genome analysis for new therapeutic interventions. Mol Cancer Ther. 2005;4:1636–1643.PubMedCrossRefGoogle Scholar
  22. 22.
    Nishio K, Arao T, Shimoyama T, et al. Translational studies for target-based drugs. Cancer Chemother Pharmacol. 2005;56(suppl 1):90–93.PubMedCrossRefGoogle Scholar
  23. 23.
    Katoh M, Katoh M. Bioinformatics for cancer management in the post-genome era. Technol Cancer Res Treat. 2006;5:169–175.PubMedGoogle Scholar
  24. 24.
    Miles AK, Matharoo-Ball B, Li G, Ahmad M, Rees RC. The identification of human tumour antigens: current status and future developments. Cancer Immunol Immunother. 2006;55:996–1003.PubMedCrossRefGoogle Scholar
  25. 25.
    Quackenbush J. Microarray analysis and tumor classification. N Engl J Med. 2006;354:2463–2472.PubMedCrossRefGoogle Scholar
  26. 26.
    Redfern O, Grant A, Maibaum M, Orengo C. Survey of current protein family databases and their application in comparative, structural and functional genomics. J Chromatogr B Anal Technol Biomed Life Sci. 2005;815:97–107.CrossRefGoogle Scholar
  27. 27.
    Iqbal O, Fareed J. Clinical applications of bioinformatics, genomics, and pharmacogenomics. Methods Mol Biol. 2006;316:159–177.PubMedGoogle Scholar
  28. 28.
    Reeves GA, Thornton JM. BioSapiens Network of Excellence. Integrating biological data through the genome. Hum Mol Genet. 2006;15(Special No. 1):R81–R87.PubMedCrossRefGoogle Scholar
  29. 29.
    Waggoner A. Fluorescent labels for proteomics and genomics. Curr Opin Chem Biol. 2006;10:62–66.PubMedCrossRefGoogle Scholar
  30. 30.
    Ritchie MD. Bioinformatics approaches for detecting gene-gene and gene-environment interactions in studies of human disease. Neurosurg Focus. 2005;19:E2.PubMedCrossRefGoogle Scholar
  31. 31.
    Hanai T, Hamada H, Okamoto M. Application of bioinformatics for DNA microarray data to bioscience, bioengineering and medical fields. J Biosci Bioeng. 2006; 101:377–384.PubMedCrossRefGoogle Scholar
  32. 32.
    Goodman N. Biological data becomes computer literate: new advances in bioinformatics. Curr Opin Biotechnol. 2002;13:68–71.PubMedCrossRefGoogle Scholar
  33. 33.
    Ness SA. Basic microarray analysis: strategies for successful experiments. Methods Mol Biol. 2006;316:13–33.PubMedGoogle Scholar
  34. 34.
    Perco P, Rapberger R, Siehs C, et al. Transforming omics data into context: bioinformatics on genomics and proteomics raw data. Electrophoresis. 2006;27:2659–2675.PubMedCrossRefGoogle Scholar
  35. 35.
    Haoudi A, Bensmail H. Bioinformatics and data mining in proteomics. Expert Rev Proteomics. 2006;3:333–343.PubMedCrossRefGoogle Scholar
  36. 36.
    Ivanov AS, Veselovsky AV, Dubanov AV, Skvortsov VS. Bioinformatics platform development: from gene to lead compound. Methods Mol Biol. 2006;316:389–431.PubMedGoogle Scholar
  37. 37.
    Teufel A, Krupp M, Weinmann A, Galle PR. Current bioinformatics tools in genomic biomedical research (review). Int J Mol Med. 2006;17:967–973.PubMedGoogle Scholar
  38. 38.
    Regnstrom K, Burgess DJ. Pharmacogenomics and its potential impact on drug and formulation development. Crit Rev Ther Drug Carrier Syst. 2005;22:465–492.PubMedGoogle Scholar
  39. 39.
    Willard HF, Angrist M, Ginsburg GS. Genomic medicine: genetic variation and its impact on the future of health care. Philos Trans R Soc Lond B Biol Sci. 2005;360:1543–1550.PubMedCrossRefGoogle Scholar
  40. 40.
    Garraway LA, Seller WR. From integrated genomics to tumor lineage dependency. Cancer Res. 2006;66:2506–2508.PubMedCrossRefGoogle Scholar
  41. 41.
    McDunn JE, Chung TP, Laramie JM, Townsend RR, Cobb JP. Physiologic genomics. Surgery. 2006;139:133–139.PubMedCrossRefGoogle Scholar
  42. 42.
    Tost J, Gut IG. Genotyping single nucleotide polymorphisms by mass spectrometry. Mass Spectrom Rev. 2002;21:388–418.PubMedCrossRefGoogle Scholar
  43. 43.
    Thomas DC, Haile RW, Duggan D. Recent developments in genomewide association scans: a workshop summary and review. Am J Hum Genet. 2005;77:337–345.PubMedCrossRefGoogle Scholar
  44. 44.
    Bernig T, Chanock SJ. Challenges of SNP genotyping and genetic variation: its future role in diagnosis and treatment of cancer. Expert Rev Mol Diagn. 2006;6:319–331.PubMedCrossRefGoogle Scholar
  45. 45.
    Anderson S, Bankier AT, Barrell BG, et al. Sequence and organization of the human mitochondrial genome. Nature. 1981;290:457–465.PubMedCrossRefGoogle Scholar
  46. 46.
    Mundy C. The human genome project: a historical perspective. Pharmacogenomics. 2001;2:37–49.PubMedCrossRefGoogle Scholar
  47. 47.
    International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature. 2004;431:931–945.CrossRefGoogle Scholar
  48. 48.
    Baxevanis AD. Using genomic databases for sequence-based biological discovery. Mol Med. 2003;9:185–192.PubMedGoogle Scholar
  49. 49.
    The International HapMap Consortium. The International HapMap Project. Nature. 2003;426:789–796.CrossRefGoogle Scholar
  50. 50.
    Thorisson GA, Stein LD. The SNP Consortium website: past, present and future. Nucleic Acids Res. 2003;31:124–127.PubMedCrossRefGoogle Scholar
  51. 51.
    Liu T, Johnson JA, Casella G, Wu R. Sequencing complex diseases with HapMap. Genetics. 2004;168:503–511.PubMedCrossRefGoogle Scholar
  52. 52.
    Riva A, Kohane IS. A SNP-centric database for the investigation of the human genome. BMC Bioinform. 2004;5:33.CrossRefGoogle Scholar
  53. 53.
    Kong X, Matise TC. MAP-O-MAT: internet-based linkage mapping. Bioinformatics. 2005;21:557–559.PubMedCrossRefGoogle Scholar
  54. 54.
    Brandon MC, Lott MT, Nguyen KC, et al. MITOMAP: a human mitochondrial genome database-2004 update. Nucleic Acids Res. 2005;33:D611–D613.PubMedCrossRefGoogle Scholar
  55. 55.
    Carulli JP, Artinger M, Swain PM, et al. High throughput analysis of differential gene expression. J Cell Biochem Suppl. 1998;30–31:286–296.PubMedCrossRefGoogle Scholar
  56. 56.
    Scheel J, Von Brevern MC, Horlein A, et al. Yellow pages to the transcriptome. Pharmacogenomics. 2002;3:791–807.PubMedCrossRefGoogle Scholar
  57. 57.
    Hedge PS, White IR, Debouck C. Interplay of transcriptomics and proteomics. Curr Opin Biotechnol. 2003;14:647–651.CrossRefGoogle Scholar
  58. 58.
    Suzuki M, Hayashizaki Y. Mouse-centric comparative transcriptomics of protein coding and non-coding RNAs. Bioessays. 2004;26:833–843.PubMedCrossRefGoogle Scholar
  59. 59.
    Breitling R, Herzyk P. Biological master games: using biologists’ reasoning to guide algorithm development for integrated functional genomics. OMICS. 2005;9:225–232.PubMedCrossRefGoogle Scholar
  60. 60.
    Storck T, von Brevern MC, Behrens CK, Scheel J, Bach A. Transcriptomics in predictive toxicology. Curr Opin Drug Discov Dev. 2002;5:90–97.Google Scholar
  61. 61.
    Hu YF, Kaplow J, He Y. From traditional biomarkers to transcriptome analysis in drug development. Curr Mol Med. 2005;5:29–38.PubMedCrossRefGoogle Scholar
  62. 62.
    Kralj M, Kraljevic S, Sedic M, Kurjak A, Pavelic K. Global approach to perinatal medicine: functional genomics and proteomics. J Perinat Med. 2005;33:5–16.PubMedCrossRefGoogle Scholar
  63. 63.
    Morgan KT, Jayyosi Z, Hower MA, et al. The hepatic transcriptome as a window on whole-body physiology and pathophysiology. Toxicol Pathol. 2005;33:136–145.PubMedCrossRefGoogle Scholar
  64. 64.
    Jansen BJ, Schalkwijk J. Transcriptomics and proteomics of human skin. Brief Funct Genomic Proteomic. 2003;1:326–341.PubMedCrossRefGoogle Scholar
  65. 65.
    Liang P, Zhu W, Zhang X, et al. Differential display using one-base anchored oligo-dT primers. Nucleic Acids Res. 1994;22:5763–5764.PubMedCrossRefGoogle Scholar
  66. 66.
    Ahmed FE. Molecular techniques for studying gene expression in carcinogenesis. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2002;20:77–116.PubMedGoogle Scholar
  67. 67.
    Muller-Hagen G, Beinert T, Sommer A. Aspects of lung cancer gene expression profiling. Curr Opin Drug Discov Dev. 2004;7:290–303.Google Scholar
  68. 68.
    Anderson JS, Mann M. Functional genomics by mass spectrometry. FEBS Lett. 2000;480:25–31CrossRefGoogle Scholar
  69. 69.
    Liotta LA, Petricoin EF III. The promise of proteomics. Clin Adv Hematol Oncol. 2003;1:460–462.PubMedGoogle Scholar
  70. 70.
    Jain KK. Role of oncoproteomics in the personalized management of cancer. Expert Rev Proteomics. 2004;1:49–55.PubMedCrossRefGoogle Scholar
  71. 71.
    Hanash S. Disease proteomics. Nature. 2003;422:226–232.PubMedCrossRefGoogle Scholar
  72. 72.
    Baggerman G, Vierstraete E, De Loof A, Schoofs L. Gel-based versus gel-free proteomics: a review. Comb Chem High Throughput Screen. 2005;8:669–677.PubMedCrossRefGoogle Scholar
  73. 73.
    Calvo KR, Liotta LA, Petricoin EF. Clinical proteomics: from biomarker discovery and cell signaling profiles to individualized personal therapy. Biosci Rep. 2005;25:107–125.PubMedCrossRefGoogle Scholar
  74. 74.
    Brown RE. Morphoproteomics: exposing protein circuitries in tumors to identify potential therapeutic targets in cancer patients. Expert Rev Proteomics. 2005;2:337–348.PubMedCrossRefGoogle Scholar
  75. 75.
    Kalia A, Gupta RP. Proteomics: a paradigm shift. Crit Rev Biotechnol. 2005;25:173–198.PubMedCrossRefGoogle Scholar
  76. 76.
    Scaros O, Fisler R. Biomarker technology roundup: from discovery to clinical applications, a broad set of tools is required to translate from the lab to the clinic. Biotechniques. 2005;Suppl:30-32.Google Scholar
  77. 77.
    Clarke W, Chan DW. ProteinChips: the essential tools for proteomic biomarker discovery and future clinical diagnostics. Clin Chem Lab Med. 2005;43:1279–1280.PubMedCrossRefGoogle Scholar
  78. 78.
    Kolch W, Mischak H, Pitt AR. The molecular make-up of a tumour: proteomics in cancer research. Clin Sci (Lond). 2005;108:369–383.CrossRefGoogle Scholar
  79. 79.
    Patel PS, Telang SD, Rawal RM, Shah MH. A review of proteomics in cancer research. Asian Pac J Cancer Prev. 2005;6:113–117.PubMedGoogle Scholar
  80. 80.
    Roboz J. Mass spectrometry in diagnostic oncoproteomics. Cancer Invest. 2005;23:465–478.PubMedGoogle Scholar
  81. 81.
    Waldburg N, Kahne T, Reisenauer A, et al. Clinical proteomics in lung diseases. Pathol Res Pract. 2004;200:147–154.PubMedCrossRefGoogle Scholar
  82. 82.
    Stroncek DF, Burns C, Martin BM, et al. Advancing cancer biotherapy with proteomics. J Immunother. 2005;28:183–192..PubMedCrossRefGoogle Scholar
  83. 83.
    Fleming K, Kelley LA, Islam SA, et al. The proteome: structure, function and evolution. Philos Trans R Soc Lond B Biol Sci. 2006;361:441–451.PubMedCrossRefGoogle Scholar
  84. 84.
    Domon B, Aebersold R. Mass spectrometry and protein analysis. Science. 2006;312:212–217.PubMedCrossRefGoogle Scholar
  85. 85.
    Gulmann C, Sheehan KM, Kay EW, Liotta LA, Petricoin EF 3rd. Array-based proteomics: mapping of protein circuitries for diagnostics, prognostics, and therapy guidance in cancer. J Pathol. 2006;208:595–606.PubMedCrossRefGoogle Scholar
  86. 86.
    Kingsmore SF. Multiplexed protein measurement: technologies and applications of protein and antibody arrays. Nat Rev Drug Discov. 2006;5:310–320.PubMedCrossRefGoogle Scholar
  87. 87.
    Davis CD, Milner J. Frontiers in nutrigenomics, proteomics, metabolomics and cancer prevention. Mutat Res. 2004;551:51–64.PubMedGoogle Scholar
  88. 88.
    Griffin JL, Bollard ME. Metabonomics: its potential as a tool in toxicology for safety assessment and data integration. Curr Drug Metab. 2004;5:389–398.PubMedCrossRefGoogle Scholar
  89. 89.
    Rochfort S. Metabolomics reviewed: a new “omics” platform technology for systems biology and implications for natural products research. J Nat Prod. 2005;68:1813–1820.PubMedCrossRefGoogle Scholar
  90. 90.
    Griffin JL. The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball? Philos Trans R Soc Lond B Biol Sci. 2006;361:147–161.PubMedCrossRefGoogle Scholar
  91. 91.
    Mahal LK. Glycomics: towards bioinformatics approaches to understanding glycosylation. Anticancer Agents Med Chem. 2008;8:37–51.PubMedCrossRefGoogle Scholar
  92. 92.
    Packer NH, von der Lieth C-W, Aoki-Kinoshita KF, et al. Frontiers in glycomics: bioinformatics and biomarkers in disease. Proteomics. 2008;8:8–20.PubMedCrossRefGoogle Scholar
  93. 93.
    Pilobello KT, Mahal LK. Deciphering the glycocode: the complexity and analytical challenge of glycomics. Curr Opin Chem Biol. 2007;11:300–305.PubMedCrossRefGoogle Scholar
  94. 94.
    Bernas T, Gregori G, Asem EK, Robinson JP. Integrating cytomics and proteomics. Mol Cell Protemics. 2006;5:2–13.CrossRefGoogle Scholar
  95. 95.
    Gomase VS, Tagore S. Cytomics. Curr Drug Metab. 2008;9:263–266.PubMedCrossRefGoogle Scholar
  96. 96.
    Tarnok A. Slide-based cytometry for cytomics: a minireview. Cytometry A. 2006;69A:555–562.CrossRefGoogle Scholar
  97. 97.
    Valet G. Cytomics as a new potential for drug discovery. Drug Discov Today. 2006;11:785–791.PubMedCrossRefGoogle Scholar
  98. 98.
    Tarnok A, Bosci J, Brockhoff G. Cytomics: importance of multimodal analysis of cell function and proliferation in oncology. Cell Prolif. 2006;39:495–505.PubMedCrossRefGoogle Scholar
  99. 99.
    Gomase VS, Tagore S. Physiomics. Curr Drug Metab. 2008;9:259–262.PubMedCrossRefGoogle Scholar
  100. 100.
    Porterfield DM. Measuring metabolism and biophysical flux in the tissue, cellular and sub-cellular domains: recent developments in self-referencing amperometry for physiological sensing. Biosens Bioelectron. 2007;15:1186–1196.CrossRefGoogle Scholar
  101. 101.
    ul Haque A, Chatni MR, Li G, Porterfield DM. Biochips and other microtechnologies for physiomics. Expert Rev Proteomics. 2007;4:553–463.PubMedCrossRefGoogle Scholar
  102. 102.
    Ramsay G. DNA chips: state-of-the art. Nat Biotechnol. 1997;16:40–44.CrossRefGoogle Scholar
  103. 103.
    Duggan DJ, Bittner M, Chen Y, Meltzer P, Trent JM. Expression profiling using cDNA microarrays. Nat Genet. 1999;21(suppl 1):10–14.PubMedCrossRefGoogle Scholar
  104. 104.
    Chen l, Ren J. High-throughput DNA analysis by microchip electrophoresis. Comb Chem High Throughput Screen. 2004;7:29–43.PubMedGoogle Scholar
  105. 105.
    Heller MJ. DNA microarray technology: devices, systems, and applications. Annu Rev Biomed Eng. 2002;4:129–153.PubMedCrossRefGoogle Scholar
  106. 106.
    Obeid PJ, Christopoulos TK. Microfabricated systems for nucleic acid analysis.Crit Rev Clin Lab Sci. 2004;41:429–465.PubMedCrossRefGoogle Scholar
  107. 107.
    Shi L, Tong W, Goodsaid F, et al. QA/QC: challenges and pitfalls facing the microarray community and regulatory agencies. Expert Rev Mol Diagn. 2004;4:761–777.PubMedCrossRefGoogle Scholar
  108. 108.
    Zhumabayeva B, Chenchik A, Siebert PD, Herrler M. Disease profiling arrays: reverse format cDNA arrays complimentary to microarrays. Adv Biochem Eng Biotechnol. 2004; 86:191–213.PubMedGoogle Scholar
  109. 109.
    Brentani RR, Carraro DM, Verjovski-Almeida S, et al. Gene expression arrays in cancer research: methods and applications. Crit Rev Oncol Hematol. 2005;54:95–105.PubMedCrossRefGoogle Scholar
  110. 110.
    Diatchenko L, Lau YF, Campbell AP, et al. Suppression subtractive hybridization: a method for generating differentially regulated or tissue-specific cDNA probes and libraries. Proc Natl Acad Sci USA. 1996;93:6025–6030.PubMedCrossRefGoogle Scholar
  111. 111.
    Wang X, Feuerstein GZ. Suppression subtractive hybridization: application in the discovery of novel pharmacological targets. Pharmacogenomics. 2000;1:101–108.PubMedCrossRefGoogle Scholar
  112. 112.
    Velculescu VE, Vogelstein B, Kinzler KW. Analyzing uncharted transcriptomes with SAGE. Trends Genet. 2000;16:423–425.PubMedCrossRefGoogle Scholar
  113. 113.
    Polyak K, Riggins GJ. Gene discovery using the serial analysis of gene expression technique: implications for cancer research. J Clin Oncol. 2001;19:2948–2958.PubMedGoogle Scholar
  114. 114.
    Riggins GJ. Using serial analysis of gene expression to identify tumor markers and antigens. Dis Markers. 2001;17:41–48.PubMedGoogle Scholar
  115. 115.
    Vihinen M. Bioinformatics in proteomics. Biomol Eng. 2001;18:241–248.PubMedCrossRefGoogle Scholar
  116. 116.
    Rabilloud T. Two-dimensional gel electrophoresis in proteomics: old, old-fashioned, but it still climbs up the mountains. Proteomics. 2002;2:3–10.PubMedCrossRefGoogle Scholar
  117. 117.
    Nicholson JK. Reviewers peering from under a pile of ‘omics’ data. Nature. 2006;440:992.PubMedCrossRefGoogle Scholar
  118. 118.
    Belacel N, Wang Q, Cuperlovic-Culf M. Clustering methods for microarray gene expression data. OMICS. 2006;10:507–531.PubMedCrossRefGoogle Scholar
  119. 119.
    Taylor CF. Progress in standards for reporting omics data. Curr Opin Drug Discov Dev. 2007;10:254–263.Google Scholar
  120. 120.
    Zhang X, Li L, Wei D, Yap Y, Chen F. Moving cancer diagnostics from bench to bedside. Trends Biotechnol. 2007;25:166–173.PubMedCrossRefGoogle Scholar
  121. 121.
    Culhane AC, Howlin J. Molecular profiling of breast cancer: transcriptomic studies and beyond. Cel Mol Life Sci. 2007;64;3185–3200.CrossRefGoogle Scholar
  122. 122.
    Finn WG. Diagnostic pathology and laboratory medicine in the age of “omics”: a paper from the 2006 William Beaumont Hospital Symposium on Molecular Pathology. J Mol Diagn. 2007;9:431–436.PubMedCrossRefGoogle Scholar
  123. 123.
    Wilkes T, Laux H, Foy CA. Microarray data quality-a review of current developments. OMICS. 2007;11:1–13.PubMedCrossRefGoogle Scholar
  124. 124.
    Tanaka H. Bioinformatics and genomics for opening new perspective for personalized care. Stud Health Technol Inform. 2008;134:47–58.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Timothy Craig Allen
    • 1
  • Philip T. Cagle
    • 2
  1. 1.Department of PathologyUniversity of Texas Health Science Center at TylerTylerUSA
  2. 2.Pathology and Laboratory MedicineWeill Medical College of Cornell UniversityNew YorkUSA

Personalised recommendations