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Predicting Functional Relationships in Osteoblasts JACOB M. LUBER1, 2, CATHERINE SHARP2, KB CHOI2, CHERYL ACKERT-BICKNELL2,3 & MATTHEW A. HIBBS1,2 1DEPARTMENT 2THE OF COMPUTER SCIENCE, TRINITY UNIVERSITY, SAN ANTONIO, TEXAS 78212 USA JACKSON LABORATORY, BAR HARBOR, MAINE 04609 USA 3UNIVERSITY OF ROCHESTER MEDICAL CENTER, ROCHESTER, NEW YORK 14642 USA CORRESPONDING AUTHOR EMAIL: [email protected] Tissue Context Specificity Bicknell & Hibbs, 2012 Functional Relationship Networks Node for each gene Edges between functionally related (or predicted genes) Correlation-based measures examine trends, rather than absolute values Unrelated pairs not connected Steps to Predict Improved Pathways Mouse Biology Genomic Data Features Gold Standard Heterogeneous Data Integration Machine Learning Predictions! Machine Learning & Context Specificity We need to consider both: What Context Our Data Come From & All Mouse Data Tissue Specific Data (Bone Element) How We Handle Ground Truth ROC Curves Bone Only Model All Tissue Model Curated GS MODEL TRAINED ON ALL TISSUE DATA WITH A MANUALLY CURATED GOLD STANDARD MODEL TRAINED ON BONE ELEMENT DATA WITH A MANUALLY CURATED GOLD STANDARD GO Derived GS MODEL TRAINED ON ALL TISSUE DATA WITH A GO DERIVED GOLD STANDARD MODEL TRAINED ON BONE ELEMENT DATA WITH A GO DERIVED GOLD STANDARD ROC Curves Bone Only Model All Tissue Model Curated GS GO Derived GS PR Curves Bone Only Model All Tissue Model Curated GS GO Derived GS WNT Signaling (KEGG) WNT Signaling Bone Only Model All Tissue Model Curated GS GO Derived GS BMP Signaling (KEGG) BMP Signaling Bone Only Model All Tissue Model Curated GS GO Derived GS Key Takeaways ■ Predictions made by the four classifiers are very dissimilar ■ Likely that some of the highly predicted edges in classifiers trained on all data may not actually be related within the context of bone biology ■ Literature evidence suggests classifiers trained on manually curated data and applied to only bone element data provides most accurate picture of bone biology (Cain et. al.) ■ Curated gold standard contains edges not supported by bone only data---suggesting that only a subset of FRs in the literature are supported by co-expression data ■ Methods are a next step of current state of the art methods like FNTM Acknowledgements ■ Matt Hibbs ■ Carol Bult ■ KB Choi ■ Adam Lavertu, Evan Cofer ■ Cheryl Ackert-Bicknell, Catherine Sharp ■ Troyanskaya Group & Casey Greene ■ Huttenhower Group ■ NIH ■ NSF ■ Trinity University Mach Research Fellowship More Details @ scholar.harvard.edu/~jluber Contact Me @ [email protected] Gaussian Fits