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Classification Models based on Graphs in Biomedicine

Classification Models based on Graphs in Biomedicine. Cristian R. Munteanu, Ph.D. Biomedicine Researcher RNASA-IMEDIR, TIC, University of A Coruña http://miaja.tic.udc.es | muntisa@gmail.com. Outlines. Networks and Graphs Graphs in Biomedicine Graph Software Model Online Implementation

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Classification Models based on Graphs in Biomedicine

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  1. Classification Models based on Graphs in Biomedicine Cristian R. Munteanu, Ph.D. Biomedicine Researcher RNASA-IMEDIR, TIC, University of A Coruña http://miaja.tic.udc.es | muntisa@gmail.com

  2. Outlines • Networks and Graphs • Graphs in Biomedicine • Graph Software • Model Online Implementation • Publications Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  3. Networks and Graphs • Network- any interconnected group or system, any method of sharing information between two systems • Graph - symbolic representation of a network and its connectivity; it implies an abstraction of the reality so it can be simplified as a set of nodes (vertex) connected by edges (links) • Topological Indices (TIs) - numerical parameters of the graph which characterize its topology/geometry/ structure TIs codify the INFORMATION about a real network Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  4. Networks and Graphs Graph Matrices Connectivities, node distances, node degrees, node transition probabilities Real Network Graph Topological Indices (TIs) Classification Models (using General Discriminant Analysis, Neural Networks, Machine Learning, etc.) Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  5. Graphs in Biomedicine Disease Fingerprints New Protein primary/secondary/3D structure, any other property Blood Serum Proteome Mass Spectrum Medical device outputs (EEG, etc) New DNA/RNA nucleotide sequences mRNA Microarrays Single Nucleotide Polymorphisms (SNPs) rs4682148rs7631540rs6808291 rs1486012 rs9824856 3 2 0 2 0 C1G2A3C4T5T6T7C8G9C10C11C12G13A14A15T16C17G18A19C20A21 Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  6. Graphs in Biomedicine Proteins / Proteome Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  7. S2SNet • S2SNettransforms any character sequences in Star Network Topological Indices: Shannon Entropy of Markov Matrices (Sh), Trace of connectivity matrix (Tr), Harary number (H), Wiener index (W), Gutman index (S6), Schultz index (S), Moreau-Brotoindices, Balaban distance connectivity index (J), Kier-Hall connectivity indices (0,2-5X) and Randic connectivity index (1X) wxPython Graphviz Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  8. MCeCoNet • Introduces a new class of centralities based on the Markov Topological indices and node transition probabilities • Calculates the TIs and the node centralities during a network attack • *Metabolic network wxPython Graphviz Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com gnuplot

  9. Graphs in CRC Prediction Multi-target QPDR classification model for human breast and colon cancer-related proteins using star graph topological indices, Journal of Theoretical Biology 257 (2009) 303–311 • 189 HBC/CRC cancer proteins and 865 non-cancer proteins from an experimental analysis of 13,023 genes in 11 breast and 11 colorectal cancers • Protein primary sequences => Star Graphs => Topological indices => Statistical methods => Classification Model (Quantitative Proteome - Disease Relationship, QPDR) • GDA - General Discriminant Analysis Method • Forward Stepwise model type • 75% cases for training and 25% cases for cross-validation • 89.9%, 90.3% and 90.0% for the training, cross-validation and full sets CRC-score = -20.8+1.7*Tr3e+124.8*Se-Je+0.2*X2e-45.9*X5e Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  10. Model Online Implementation Bio-AIMS Portal | http://miaja.tic.udc.es/Bio-AIMS/ Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  11. Model Online ImplementationBio-AIMS Portal | http://miaja.tic.udc.es/Bio-AIMS/ Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  12. Publications • Star Graphs of Protein Sequences and Proteome Mass Spectra in Cancer Prediction, Current Proteomics 6(4), in press (2009) • Generalized Lattice Graphs for 2D-Visualization of Biological Information, J. Theor. Biol. 261(1), 136-147 (2009) • Book chapter: Protein Graphs in Cancer Prediction, in An Omics Perspective of Cancer, W.C.S. Cho (ed.), Springer, in press (2009) • Book Chapter: Markov Entropy Centrality: Chemical, Biological, Crime and Legislative Networks, in Information theory of Complex Networks: Statistical Methods and Applications, Springer, in press (2009) Classification Models based on Graphs in Biomedicine Cristian R. Munteanu | http://miaja.tic.udc.es | muntisa@gmail.com

  13. Thank you Cristian R. Munteanu, Ph.D. Biomedicine Researcher RNASA-IMEDIR, TIC , University of A Coruña http://miaja.tic.udc.es | muntisa@gmail.com

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