341: Introduction to Bioinformatics

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

2. Topics • 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 2 2

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. Software tools • Network analysis and modeling:

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. Topics • 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 10 10 10