clustering algorithms to make sense of microarray data: systems analyses in biology

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Clustering Algorithms to make sense of Microarray data: Systems Analyses in Biology Doug Welsh and Brian Davis BioQuest Workshop Beloit Wisconsin, June 2004

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Clustering Algorithms to make sense of Microarray data: Systems Analyses in Biology. Doug Welsh and Brian Davis BioQuest Workshop Beloit Wisconsin, June 2004. Biological Questions. What are the differences between cancer cells and normal cells? - PowerPoint PPT Presentation

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Page 1: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Clustering Algorithms to make sense of Microarray data:

Systems Analyses in Biology

Doug Welsh and Brian Davis BioQuest Workshop

Beloit Wisconsin, June 2004

Page 2: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Biological QuestionsWhat are the differences between cancer cells and normal cells? What are the differences in gene expression between

cancer cells and normal cells? Can you guess at the cellular sub-systems that may

be affected by cancer?What are the cellular processes (pathways) that

might differ between cancer cells and normal cells?

• Can you guess at the components (proteins) of the pathways that might be involved in cancer

Page 3: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

GoalsSystems Biology (shift focus among levels of knowledge)Biology Gene Expression (technique) Pathways DNA Replication Individual Proteins

Math Clustering Algorithms (theory and technique) Statistics

Medicine (human phenotype)

Page 4: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Goals

Knowledge

Cluster

Stats Math

Physics

Optics

Biology

Medicine

Cell Biology

Pathway

ProteinRobotics

Programming

Page 5: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Goals

Knowledge

Cluster

Stats Math

Physics

Optics

Biology

Medicine

Cell Biology

Pathway

Protein“Tools”

Robotics

Programming

Page 6: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Problem Space

Bedrock web site: http://bioquest.org/bedrock/problem_spaces/

Page 7: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Problem SpaceDNA Replication

Cell Cycle(Depends on Paper)

Microarray FilesGene Annotation

Microarray AnalysisPathway Analysis

Statistical Analysis

Page 8: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Assumptions

Assume co-expression of genes has significance.We can generate A LOT of data.

Wheat and Chaff

Clustering algorithms and viewing software allow a researcher to focus on subsets of (“significant”) data at a time.

Page 9: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

ProjectPaper: Singh D. et al. (2002) Gene expression correlates of clinical prostate cancer behavior. Cancer Cell Mar;1(2):203-9.Questions: What is the testable hypothesis? How is it tested? What are the results? Are the conclusions valid?Are there other (better?) ways to test this hypothesis? Are there better hypotheses to formulate?

Page 10: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Biological QuestionsWhat are the differences between cancer cells and normal cells? What are the differences in gene expression between

cancer cells and normal cells? Can you guess at the cellular sub-systems that may

be affected by cancer?What are the cellular processes (pathways) that

might differ between cancer cells and normal cells?

• Can you guess at the components (proteins) of the pathways that might be involved in cancer

Page 13: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

AnalysisClustering may reveal organizational unitsWhat are these proteins and what processes are they involved in?

Page 14: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Next StepsHand off clusters of organizational units to Doug (GeneMAPP and MAPPFinder: What are these proteins in the context of cellular pathways?)…Investigate interesting single proteins (e.g., with NCBI tools).Are these proteins conserved? (do yeast get cancer?)What is the molecular basis of cancer?

Page 15: Clustering Algorithms to make sense of Microarray data:  Systems Analyses in Biology

Goals

Knowledge

Cluster

Stats Math

Physics

Optics

Biology

Medicine

Cell Biology

Pathway

ProteinRobotics