1. 341: Introduction to Bioinformatics Dr. Natasa Przulj Deaprtment of Computing Imperial College London natasha@imperial.ac.uk

2. 2 2 Topics 2 Introduction to biology (cell, DNA, RNA, genes, proteins) Sequencing and genomics (sequencing technology, sequence alignment algorithms) Functional genomics and microarray analysis (array technology, statistics, clustering and classification) Introduction to graph theory Protein 3D structure Introduction to biological networks Network comparisons: network properties  Network/node centralities  Network motifs and graphlets Network models Network alignment Software tools for network analysis OPTIONAL: Graph clustering; Interplay of topology & biology

3. Software tools Network analysis and modeling: –mfinder/mDraw –MAVisto (Motif Analysis and Visualization Tool) –FANMOD (fast network motif detection) –TopNet/tYNA (TopNet-like Yale Network Analyzer) –Pajek (i.e., spider) –GraphCrunch Network alignment and comparison: –NetAlign –PathBLAST Clustering of networks into modules: –CFinder General-purpose: –Cytoscape …

4. Software tools Network analysis and modeling: –mfinder/mDraw, MAVisto, and FANMOD: Main purpose: motif search No global network properties Can generate some net. models, but does not compare to data –Pajek: global network properties very limited local network analysis capabilities (its search for subgraphs is limited to 3-4-node rings only) Can generate some net. models, but does not compare to data –tYNA: Both global and local network analyses are limited (only the statistics of global network properties (no distributions) and only three network motif types

5. Software tools Network analysis and modeling: –GraphCrunch Global network properties: –Degree distribution –Average clustering coefficient and clustering spectrum –Average diameter and distance spectrum Local network properties –Graphlet counts –RGF-distance –GDD-agreement Generates five different network models Compares real-world with model networks

6. Network analysis and modeling: Software tools

7. Example output of GraphCrunch

8. Software tools Network alignment and comparison: –NetAlign Web-based tool for comparative analysis of PPI networks Compares a query PPI network with a target PPI network by combining interaction topology and sequence similarity to identify conserved network substructures –PathBLAST Network alignment and search tool for comparing PPI networks across species to identify protein pathways and complexes that have been conserved by evolution –You can get the code for other algorithms! Clustering of networks into modules: –CFinder Searches for dense clusters, while allowing for any node to belong to more than one cluster There should exist tools that can cluster nets and compute enrichments

9. Software tools General-purpose –Cytoscape General-purpose, open-source software environment for the large scale integration of molecular interaction network data Network visualization (a variety of automated network layout algorithms) Links a network to molecular interaction and functional databases (transfer of annotations) Data integration … Please review the course material for some additional tools (e.g., BioLayout Express 3D, tools for computing centralities) Please explore other available tools

10. 10 Topics 10 Introduction to biology (cell, DNA, RNA, genes, proteins) Sequencing and genomics (sequencing technology, sequence alignment algorithms) Functional genomics and microarray analysis (array technology, statistics, clustering and classification) Introduction to graph theory Protein 3D structure Introduction to biological networks Network comparisons: network properties  Network/node centralities  Network motifs and graphlets Network models Network alignment Software tools for network analysis OPTIONAL: Graph clustering; Interplay of topology & biology