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Andrey Alexeyenko M edical E pidemiology and B iostatistics Network biology and cancer data integration.

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Presentation on theme: "Andrey Alexeyenko M edical E pidemiology and B iostatistics Network biology and cancer data integration."— Presentation transcript:

1 Andrey Alexeyenko M edical E pidemiology and B iostatistics Network biology and cancer data integration

2 FunCoup: on-line interactome resource Andrey Alexeyenko and Erik L.L. Sonnhammer (2009) Global networks of functional coupling in eukaryotes from comprehensive data integration. Genome Research. http://FunCoup.sbc.su.se

3 Single molecular markers are often far from perfect. Combinations (signatures) should perform better. How to select optimal combinations? × Severity, Optimal treatment, Prognosis etc. Biomarker signatures in the network

4 Candidate signature in the network Biomarker candidates

5 Ready network-based signature RELAPSE = γ 1 EIF3S9 + γ 2 CRHR1 + γ 3 LYN + … + γ N KCNA5

6 Mutations: distinguishing drivers from passengers Functional coupling transcription  transcription transcription  methylation methylation  methylation mutation  methylation mutation  transcription mutation  mutation + mutated gene

7 Pathway cross-talk

8 From genes to pathways: growing confidence Inositol phosphate metabolism (KEGG) Glioblastoma (TCGARN, 2008)

9 Analysis of cancer-specific wiring Pathway network of normal vs. tumor tissues Edges connect pathways given a higher ( N>9; p 0 0.5 ) between them (seen as edge labels). Known pathways (circles) are classified as: signaling, metabolic, cancer, other disease. Blue lines: evidence from mRNA co-expression under normal conditions + ALL human & mouse data. Red lines: evidence from mRNA co-expression in expO tumor samples + ALL human data + mouse PPI. Node s i z e : number of pathway members in the network. Edge opacity : p 0. Edge t hi ck ne ss : number of gene-gene links.

10 Arrow of time: network prospective Alexeyenko et al. Zebrafish transcriptome under dioxin treatment. PLoS One. In press

11 Acknowledgements: Erik Sonnhammer’s bioinformatics group KICancer http://FunCoup.sbc.su.se

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