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Gene Expression Analysis

BI420 – Introduction to Bioinformatics. Gene Expression Analysis. Gabor T. Marth. Department of Biology, Boston College marth@bc.edu. Gene expression. Why study gene expression?. Which genes are active. at different developmental stages? in cells of different tissues?

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Gene Expression Analysis

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  1. BI420 – Introduction to Bioinformatics Gene Expression Analysis Gabor T. Marth Department of Biology, Boston College marth@bc.edu

  2. Gene expression

  3. Why study gene expression? Which genes are active • at different developmental stages? • in cells of different tissues? • at different time points in the same cell? • cells under different environmental conditions? • between normal and cancerous cells?

  4. What are expression microarrays?

  5. Expression microarrays – “physical appearance”

  6. Microarray construction

  7. cDNA preparation

  8. Expression assay

  9. Expression microarray movie DNA microarray chip animation: http://www.bio.davidson.edu/Courses/genomics/chip/chip.html

  10. Chip readout – absolute expression and ratio

  11. Chip readout – relative transcription

  12. Chip readout – example

  13. Time course experiments Experiment: measuring gene expression as oxygen gets depleted in yeast grown in a closed container

  14. Time course data

  15. Data analysis – normalization • balance fluorescent intensities of two dyes • adjust for differences in experimental conditions

  16. Normalization

  17. Log2 transformation Double or half expression now has the same magnitude

  18. Clustering – intro • Why: if the expression pattern for gene B is similar to gene A, maybe they are involved in the same or related pathway • How: Re-order expression vectors in the data set so that similar patterns are together

  19. Clustering – numerical

  20. Clustering – visual

  21. Hierarchical clustering: pair-wise similarity

  22. Hierarchical clustering: cluster construction

  23. Clustering – large example

  24. Next two classes Chapter 7. Chapter 8.

  25. Application of microarrays: classification of cancers

  26. Microarrays to detect genome copy #

  27. Protein identification Protein separation by 2D gel eletrophoresis

  28. Protein identification mass spectrometry

  29. Protein function identification protein chips: identification of proteins that bind specific chemicals

  30. Thanks Expression informatics slides courtesy of: Olga Troyanskaya, Ph.D. Department of Computer Science Lewis-Sigler Institute for Integrative Genomics Princeton University

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