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Extracting synergistic gene subnetworks from pairwise gene data

Extracting synergistic gene subnetworks from pairwise gene data. ALEXANDROS ILIADIS. Problem Discription –Input Data. 882 x 882 Weigth Matrix Element i,k is the P(Value) that G i , G k interact towards Synapse creation in C. elegans. Problem Description. All gene pairs 388521

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Extracting synergistic gene subnetworks from pairwise gene data

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  1. Extracting synergistic gene subnetworks from pairwise gene data ALEXANDROS ILIADIS

  2. Problem Discription –Input Data • 882 x 882 Weigth Matrix • Element i,k is the P(Value) that Gi ,Gk interact towards Synapse creation in C. elegans

  3. Problem Description All gene pairs 388521 IF we wanted similar Pvalues for : • Triplets 113966160 • Quadruplets 2.5044e+010 • More….Computationally Intractable • SO….. • Alternative approach in identifying Important Synergistic Subnetworks

  4. Approach • Consider the fully Interconnected graph • Nodes:Genes • Edges:P-values • Create Degree Constrained Subgraph • Extract Significantly interconnected subneworks • Bayes Ball to avoid independencies

  5. Feature Selection • Pearson Correlation • Found 167 correlate features so the original set of 441 was reduced to 274 • Also identified a group of 54 genes

  6. Degree Constrained Subgraph

  7. Optimization Problem

  8. Iterative Procedure Followed

  9. Example

  10. Convergence

  11. Convergence (cont’d)

  12. Highest Interconnected Sub-graphs • Exhaustive search for highly Interconnected Subgraphs • Graphs with the largest edge density • Density>2*Original density

  13. Avoid Independencies-Bayes’ Ball 3 2 4 1 Nodes 1 and 4 are independent given 2 and 3

  14. Results Group Post F59B2.13 Post- Flp-21 Group Pre ric-19 Group- Pre C02C2.4

  15. Results Post Ace-3 Post- Fbxb-103 Pre mai-3 Post Lim-4

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