Tuesday, 30 June 2009

New Challenges and Opportunities in Newtwork Biology

Trey Ideker *****

Richard Karp and Lee Hood are his science inspiration.
Wants to reconstruct pathways from multiple biological sources.

If you know something about a pathway you can perturb it systematically in silico and in vivo/vitro. Start was the Galactose metabolism pathway and its transcriptional control. 3 core genes. 1000 other genes were perturbed in the mutants. Transcriptional interactions were available first, now we have protein-protein interactions and we also had KEGG/metabolism.
Coloured networks - states, expression profiles, phosphorylation etc. extract sub-networks from the main network based on colour - pathway extraction.

Used phenotype for colouring the invastion of HIV.

What is the goal for the next 10 years? (What do networks actually mean?). Cell is a hairball inside in terms of its interactions.

Developed PathBLAST and NetworkBLAST using the analogy of genome assembly for network assembly. Align the orthologues between species to align the network. Works at the protein family level - removes paralogues. They are not the best algorithms now.

Moves to gene relation networks based on synthetic lethality or phenotype changes for double mutants. Gene interaction networks are logical networks (Booleans). Very little overlap between physical and genetic networks. Gene interactions are between subgraphs that are physical interactions.


ChiP-chip looking at DNA damage caused by stress and DNA repair. Finding where a TF binds by immunoprecipitation - identify the fragments that were bound to the immunoglobulin purified TFs. Problems of drift in that binding might not be significant - non-functional binding. Validated byt checking downstream loss in gene deletions but only 10% of those sites identified from ChiP-chip are verified. Spurious interactions take place close to telomeres closer than 25 kilo-base-pairs. This is condition specific so adding rapamycon can perturb it. Possibly indicates sequestration effects that make the TFs non-functional.

Using it for disease classification. Diagnose breast cancer metastasis using expression profiles. 300 patients 1/3 of whom became metastatic. Area under ROC is 65%. Heterogeneity is a problem. Little overlap between different gene sets from different studies.
Look at sequentiality or connections in protein-protein interactions.


Cancer might be the perturbation out of homeostasis.


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