Chapter 7. Computational Methods and Bioinformatic Tools

  1. Dr. Stefan Lorkowski50 and
  2. Dr. Paul Cullen51
  1. Dr. Paul Cullen51,*,
  2. Dr. Stefan Lorkowski50,*,
  3. Steffen Hennig2,*,
  4. Albert Poustka2,
  5. Georgia Panopoulou2,
  6. Hans Lehrach2,
  7. Eberhard Korsching1,
  8. Oxana Pickeral3,
  9. Ralf Herwig2,*,
  10. Alexander Kel4,*,
  11. Dmitrij Tchekmenev4,
  12. Edgar Wingender4,*,
  13. Johannes Streicher5,*,
  14. Gerd B. Müller5,
  15. Takeshi Kawashima6,
  16. Kazuhiro W. Makabe6,*,
  17. Inna Dubchak7,
  18. Hongkai Ji8,
  19. Kousaku Okubo9,*,
  20. Shoko Kawamoto10,
  21. Ellen Fricke4,
  22. Dagmar Karas4,
  23. Martin Haubrock4,
  24. Sigrid Land4,
  25. Stella Rotert4,
  26. Xin Chen11,
  27. Joan Pontius12,
  28. Eric Eveno13,
  29. Charles Auffray13,*,
  30. Charles Decraene14,
  31. Claude Chelala13,
  32. Geneviève Piétu14,
  33. Marie-Dominique Devignes15,
  34. Régine Mariage-Samson13,
  35. Sandrine Imbeaud13,
  36. Sylvie Bortoli14,
  37. Alon Amit16,*,
  38. Martin Ringwald17,
  39. Michael J. de Veer18,
  40. Bryan R. G. Williams19,*,
  41. Eldon M. Walker19,
  42. Jamie A. Davies20,
  43. Christoph Grunau21,
  44. Richard Baldock22,
  45. Duncan R. Davidson22,*,
  46. Christian J. Stoeckert Jr.23,*,
  47. Angel Pizarro23,
  48. Elisabetta Manduchi23,
  49. Gregory R. Grant23,
  50. Jonathan Crabtree24,
  51. Junmin Liu23,
  52. Phuc V. Le23,
  53. Shannon K. McWeeney23,
  54. Stephen Welle25,
  55. Catherine A. Ball26,*,
  56. David Botstein26,
  57. Gail Binkley26,
  58. Gavin J. Sherlock26,
  59. J. Michael Cherry26,
  60. Kara Dolinski26,
  61. Laurie Issel-Tarver26,
  62. Mark Schroeder26,
  63. Selina S. Dwight26,
  64. Shuai Wenig26,
  65. John C. Matese26,*,
  66. Heng Jin26,
  67. Jeremy Gollub26,
  68. Joan Hebert27,
  69. Miroslava Kaloper26,
  70. Patrick O. Brown26,
  71. Tina Hernandez-Boussard27,
  72. Anuj Kumar28,
  73. Kei-Hoi Cheung29,
  74. Luis Marenco29,
  75. Michael Snyder29,*,
  76. Nick Tosches29,
  77. Paul Bertone29,
  78. Perry Miller29,
  79. Peter Masiar29,
  80. Yang Liu29,
  81. Graziano Pesole30,
  82. Philippe Marc31,
  83. Margaret Biswas32,
  84. Paul Kersey33,
  85. Rolf Apweiler33,* and
  86. Christine Hoogland34

Published Online: 27 MAY 2004

DOI: 10.1002/352760149X.ch7

Analysing Gene Expression: A Handbook of Methods: Possibilities and Pitfalls

Analysing Gene Expression: A Handbook of Methods: Possibilities and Pitfalls

How to Cite

Cullen, P., Lorkowski, S., Hennig, S., Poustka, A., Panopoulou, G., Lehrach, H., Korsching, E., Pickeral, O., Herwig, R., Kel, A., Tchekmenev, D., Wingender, E., Streicher, J., Müller, G. B., Kawashima, T., Makabe, K. W., Dubchak, I., Ji, H., Okubo, K., Kawamoto, S., Fricke, E., Karas, D., Haubrock, M., Land, S., Rotert, S., Chen, X., Pontius, J., Eveno, E., Auffray, C., Decraene, C., Chelala, C., Piétu, G., Devignes, M.-D., Mariage-Samson, R., Imbeaud, S., Bortoli, S., Amit, A., Ringwald, M., de Veer, M. J., Williams, B. R. G., Walker, E. M., Davies, J. A., Grunau, C., Baldock, R., Davidson, D. R., Stoeckert, C. J., Pizarro, A., Manduchi, E., Grant, G. R., Crabtree, J., Liu, J., Le, P. V., McWeeney, S. K., Welle, S., Ball, C. A., Botstein, D., Binkley, G., Sherlock, G. J., Cherry, J. M., Dolinski, K., Issel-Tarver, L., Schroeder, M., Dwight, S. S., Wenig, S., Matese, J. C., Jin, H., Gollub, J., Hebert, J., Kaloper, M., Brown, P. O., Hernandez-Boussard, T., Kumar, A., Cheung, K.-H., Marenco, L., Snyder, M., Tosches, N., Bertone, P., Miller, P., Masiar, P., Liu, Y., Pesole, G., Marc, P., Biswas, M., Kersey, P., Apweiler, R. and Hoogland, C. (2002) Computational Methods and Bioinformatic Tools, in Analysing Gene Expression: A Handbook of Methods: Possibilities and Pitfalls (eds S. Lorkowski and P. Cullen), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, FRG. doi: 10.1002/352760149X.ch7

Editor Information

  1. 50

    Institute of Arteriosclerosis Research, University of Münster, Domagkstr. 3, 48149 Münster, Germany

  2. 51

    Ogham GmbH, Mendelstr. 11, 48149 Münster, Germany

Author Information

  1. 1

    University of Münster, Münster (Germany)

  2. 2

    Max Planck Institut für Molekulare Genetik, Berlin (Germany)

  3. 3

    Human Genome Sciences, Inc., Rockville (USA)

  4. 4

    BIOBASE GmbH, Wolfenbüttel (Germany)

  5. 5

    University of Vienna, Vienna (Austria)

  6. 6

    Kyoto University, Kyoto (Japan)

  7. 7

    Lawrence Berkeley National Laboratory, Berkeley (USA)

  8. 8

    Tsinghua University, Beijing (People's Republic of China)

  9. 9

    Kyushu University, Fukuoka (Japan)

  10. 10

    Medical Institute for Bioregulation, Fukuoka (Japan)

  11. 11

    The National Laboratory of Protein Engineering and Plant Genetic Engineering, Peking University, Beijing (People's Republic of China)

  12. 12

    National Center for Biotechnology Information, National Institute of Health, Bethesda (USA)

  13. 13

    Genexpress, Centre National de la Recherche Scientifique, Villejuif Cedex (France)

  14. 14

    Commisariat á l'Ènergie Atomique (CEA), Evry Cedex (France)

  15. 15

    LORIA – Langue et dialogue, Vandoeuvre les Nancy (France)

  16. 16

    Compugen Ltd., Jamesburg (USA)

  17. 17

    The Jackson Laboratory, Bar Harbor (USA)

  18. 18

    The Walter and Eliza Hall Institute of Medical Research, The Royal Melbourne Hospital, Victoria (Australia)

  19. 19

    Lerner Research Institute, Cleveland Clinic Foundation, Cleveland (USA)

  20. 20

    University of Edinburgh, Medical School, Edinburgh (UK)

  21. 21

    Institute de Génétique Humain, Montpellier (France)

  22. 22

    Western General Hospital, Edinburgh (UK)

  23. 23

    University of Pennsylvania, Philadelphia (USA)

  24. 24

    Center for Bioinformatics, University of Pennsylvania, Philadelphia (USA)

  25. 25

    University of Rochester, Rochester (USA)

  26. 26

    School of Medicine, Stanford University, Stanford (USA)

  27. 27

    Center for Clinical Sciences Research, Stanford (USA)

  28. 28

    Cellular and Developmental Biology, Yale University, New Haven (USA)

  29. 29

    School of Medicine, Yale University, New Haven (USA)

  30. 30

    University of Milan, Milan (Italy)

  31. 31

    Ecole Normale Supérieure, Paris (France)

  32. 32

    ViaLactia Biosciences Ltd., Auckland (New Zealand)

  33. 33

    European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton (UK)

  34. 34

    Swiss Institute of Bioinformatics, Geneva (Switzerland)

  35. 50

    Institute of Arteriosclerosis Research, University of Münster, Domagkstr. 3, 48149 Münster, Germany

  36. 51

    Ogham GmbH, Mendelstr. 11, 48149 Münster, Germany

*Ogham GmbH, Mendelstr. 11, 48149 Münster, Germany

Publication History

  1. Published Online: 27 MAY 2004
  2. Published Print: 1 DEC 2002

ISBN Information

Print ISBN: 9783527304882

Online ISBN: 9783527601493

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Keywords:

  • computational methods;
  • bioinformatic tools;
  • sequence tags;
  • comparative genomics;
  • data management;
  • data mining;
  • hardware;
  • software;
  • test scenario;
  • data integration;
  • gene expression clusters;
  • clustering;
  • promoter finding;
  • transcriptional regulation;
  • visualisation;
  • microscopy;
  • digital image processing;
  • RNA-based gene expression databases;
  • database management systems;
  • analyses tools;
  • protein-based gene expression databases

Summary

This chapter contains sections titled:

  • Introduction

  • Comparative expressed sequence tag analysis

    • Introduction

    • Processing expressed sequence tags prior to content analysis

    • Gene content and annotation of expressed sequence tags

    • Expressed sequence tags in comparative genomics

    • In silico subtraction using clustered sets of expressed sequence tags

    • Expressed sequence tag data repositories and cDNA clone distribution centres

  • Data management and data mining

    • Introduction

      • Current situation

      • Future development

      • Taking part in bioinformatics

      • Hardware and software demands

      • Data types, structures and processing

      • Communication structures

    • Building a test scenario

      • Microarray experiments

      • Analysing the workflow – getting things done

      • Designing the question and choosing the right tools for the answer

      • Scaling up

    • Strategies of data mining

      • Data evaluation and representation

      • Principles of query languages

      • Data mining

      • Custom solutions

    • Summary

  • Integration of heterogeneous high-throughput gene expression data

    • Introduction

    • Steps towards data integration

    • Initial steps in realising data integration

    • Conclusions

  • Cluster analysis of gene expression profiles

    • Introduction

    • Information content of gene expression clusters

    • Similarity matrices and gene expression matrices

    • Clustering algorithms

      • Hierarchical clustering

      • Self-organising maps

      • K-means

      • Gene shaving

    • Evaluation of gene expression clusters

    • Conclusion

  • Promoter finding in eukaryotic genomes

    • Introduction

    • Transcription regulation in eukaryotes

      • Promoter structure

      • Transcription factors

      • Combinatorial nature of transcription regulation

    • Databases on transcriptional regulation

    • In silico study of gene transcription regulation

      • Recognition of cis-regulatory elements

      • Recognition of composite regulatory elements

      • Recognition of promoters

    • Conclusions

  • GeneEMAC – Three-dimensional visualisation of gene expression

    • Introduction

    • Principles and basics of the GeneEMAC concept

    • Specimen preparation

      • Whole-mount in situ hybridisation

      • Embedding

      • Introduction of external markers

      • Capturing of a reference image

      • Histological sectioning

    • Microscopy and digital image processing

      • Image capturing

      • Image congruencing

      • Image segmentation

      • Generation of a three-dimensional model

    • Visualisations of models

    • Examples

    • Discussion

  • RNA-based gene expression databases and analyses tools

    • Introduction

    • ASDB – The Alternative Splicing Database

    • AsMamDB – The Alternative Splice Database of Mammals

    • BodyMap – An anatomical gene expression database of human and mouse

    • The CYTOMER® Gene Expression Database on human organs and cell types

    • Database of three-dimensional visualisation of gene expression

    • dbEST – The Database of Expressed Sequence Tags

    • DDD – Digital Differential Display

    • The Genexpress IMAGE Knowledge Base of the Human Genome and Transcriptomes

    • The GencartaTM Database

    • GEO – Gene Expression Omnibus Database

    • GXD – The Mouse Gene Expression Database

    • ISG Database – Interferon-Stimulated Gene Database

    • The Kidney Development Database

    • MAGEST – The Maboya Gene Expression Patterns and Sequence Tags Database

    • MethDB – The DNA Methylation Database

    • EMAGE – The Edinburgh Mouse Atlas Gene Expression Database

    • RAD – The RNA Abundance Database

    • The Rochester Muscle Database

    • SAGEmap – The serial analysis of gene expression tag to gene mapping database

    • SGD – The Saccharomyces Genome Database and its Expression Connection

    • SMD – The Stanford Microarray Database

    • TRIPLES – The Database of Transposon-Insertion Phenotypes, Localisation, and Expression in Saccharomyces cerevisiae

    • UTRdb and UTRsite – The Specialised Databases of Sequences and Functional Elements of 5′ and 3′-Untranslated Regions of Eukaryotic mRNAs

    • yMGV – The Yeast Microarray Global Viewer

  • Protein-based gene expression databases and analyses tools

    • Introduction to protein-based gene expression databases

    • The Proteome Analysis Database

    • SWISS-2DPAGE – A two-dimensional polyacrylamide gel electrophoresis database

  • Further gene-expression databases in the internet

  • Summary

  • References