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Gene expression analysis summary Where are we now?

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Presentation on theme: "Gene expression analysis summary Where are we now?"— Presentation transcript:

1 Gene expression analysis summary Where are we now?

2 Sample Preparation Hybridization Array design Probe design Experimental Design Buy standard Chip / Array Statistical Analysis Fit to Model (time series) Expression Index Calculation Advanced Data Analysis ClusteringPCAGene Annotation AnalysisPromoter Analysis ClassificationMeta analysisSurvival analysisRegulatory Network Comparable Gene Expression Data Normalization Image analysis The DNA Microarray Analysis Pipeline Question/hypothesis

3 DNA microarray analysis PCA (using SVD) Cluster analysis Normalization Before After

4 High-throughput applications of microarrays Gene expression * DNA re-sequencing (relative to reference) * SNP analysis * Competitive growth assays * ChIP-chip (interaction data) * Array CGH Whole genome tiling arrays Peptide arrays (interaction data, not DNA based) * De novo DNA sequencing (short)

5 Tiling microarrays Huber W, et al., Bioinformatics 2006

6 Motivation for Systems Biology

7 Interest in Systems Biology? Human genome completed PubMed abstracts

8 Systems biology and emerging properties

9 Transcriptional regulation of the Cell Cycle Simon et al. Cell 2001

10 Boehringer Mannheim metabolic map

11 Mathematical abstraction of biochemistry

12 Metabolic models

13 “Genome scale” metabolic models Genes708 Metabolites584 –Cytosolic559 –Mitochondrial164 –Extracellular121 Reactions1175 –Cytosolic702 –Mitochondrial124 –Exchange fluxes349 Forster et al. Genome Research 2003.

14 One framework for Systems Biology 1.The components. Discover all of the genes in the genome and the subset of genes, proteins, and other small molecules constituting the pathway of interest. If possible, define an initial model of the molecular interactions governing pathway function (how?). 2.Pathway perturbation. Perturb each pathway component through a series of genetic or environmental manipulations. Detect and quantify the corresponding global cellular response to each perturbation.

15 One framework for Systems Biology 3.Model Reconciliation. Integrate the observed mRNA and protein responses with the current, pathway-specific model and with the global network of protein-protein, protein-DNA, and other known physical interactions. 4.Model verification/expansion. Formulate new hypotheses to explain observations not predicted by the model. Design additional perturbation experiments to test these and iteratively repeat steps (2), (3), and (4).

16 From model to experiment and back again

17 Systems biology paradigm Aebersold R, Mann M, Nature, 2003.

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