Toward Automatically Drawn Metabolic Pathway Atlas with Peripheral Node Abstraction Algorithm

1. Toward Automatically Drawn Metabolic Pathway Atlas with Peripheral Node Abstraction Algorithm Myungha Jang, ArangRhie, and Hyun-Seok Park* Bioinformatics Laboratory, School of Engineering EwhaWomans University Seoul, Korea IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

2. Table of Contents Introduction Topological Nature of Metabolic Networks at Peripheral Nodes Node Abstraction Featured Scale-free Algorithm Experimental Results Discussion and Future Work IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

3. I. INTRODUCTION Automatic graph layout algorithms in systems biology • Abstract graph structure ⇒ visual representation • Graphical diagrams are intuitively helpful to understand biochemical reaction networks • - Node : compound, Edge : reactions • Optimal solutions : NP-hard problems IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

4. I. INTRODUCTION Focusing on Global Metabolic Pathway • A complete metabolic network indicates all the metabolic potential and capacity. • The shift of research focus: single pathways to multiple pathways. • Visualization serves an important role in understanding large scale metabolic network. • KEGGAtlas(http://www.genome.ad.jp/kegg), 2008 • Terms : Global (metabolic) pathway, Multiple pathway, Atlas IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

5. I. INTRODUCTION Our Efforts Toward Automatic Global Layout • Not enough to deal with the global pathway! • How can we obtain a complete view? • No attempts for automatic visualization for Atlas IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

6. I. INTRODUCTION How To Deal With Large-scale Metabolic Pathway? • Related work: KEGG Atlas • The map integration process is carried out manually by curators. • Based on curator’s experience • However, that metabolic networks are dynamic in nature should not be disregarded  Systematic approach is necessary IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

7. INTRODUCTION How To Deal With Large-scale Metabolic Pathway? (con’d) • Our Strategy • We provide a novel algorithmic approach in drawing multiple metabolic pathways by considering two properties: • 1. Automatic abstraction criteria: by analyzing a topological nature of metabolic networks based on the graphical property of relation distance, linear reactions were abstracted as a unit reaction. • 2. the consistency of highly connected nodes

8. II. Topological Nature of Metabolic Networks at Peripheral Nodes • We obtained 255 map data by parsing KEGG XML (KGML) documents of version 0.6 using our KGML Parser. + KGML Two terms were defined: 1. Relation degree the number of edges branching from a node 2. Relation distance a factor to measure the length between any two compounds encompassing nodes which all have relation degrees less than or equal to p (p = 2) • A dedicated analysis on peripheral nodes with low connectivity was performed. IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

9. II. Topological Nature of Metabolic Networks at Peripheral Nodes Relation Distance Term Clarification • Definition: The length between any two compounds encompassing nodes which all have relation degrees equal to p • Here, p = 2 IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

10. II. Topological Nature of Metabolic Networks at Peripheral Nodes Relation Distance Example in Map RD(C01290, C00369) = 7 • cpd:C01291 • cpd:C01290 • cpd:C16466 • cpd:C16475 • cpd:C16468 • cpd:C16470 • cpd:C16471 • cpd:C16469 • cpd:C00369 IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

11. III. Node Abstraction Featured Scale-free Algorithm Basic Motivation • Observation: 66.83% of the total compounds within the complete metabolic pathways were of low connectivity, with less than relation degree of 3. • The number of compounds with higher relation degree, i.e. more than 6 edges, was much less. Abstracting Compounds With Linear Interaction Layout Components according to High Connectivity IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

12. III. Node Abstraction Featured Scale-free Algorithm A. Abstracting Compounds With Linear Interaction • We abstracted and hid all those compounds that appear within these linear interactions. • This approach could be called “chain reduction”(M. Chimaniet al) • All green compounds in the figure will be hidden in the graph layout according to this approach. IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

13. III. Node Abstraction Featured Scale-free Algorithm B. Layout Components according to High Connectivity • Highly Connected Nodes: Nodes with relation degree bigger than 6 • LayoutHighConnectedNode()Algorithm Steps • Find a highly Connected node Nd • Each component connected to Nd is decomposed into sub-graph • Each decomposed sub-graph is treated as a super node to apply the spring-embedding algorithm • Input : Metabolic Pathway Graph • Output : coordinates of each node • voidLayoutPathway(Pathway graph) • { • IF highly connected nodes (Nd) exist in graph • LayoutHighlyConnectedNode(graph, Nd); • ELSEIF any cycle(Nc) exists in graph • AND size of cycle ≥ 6 • LayoutCircular(graph, Nc); • ELSELayoutHierarchic(graph); • } 6 3 IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

14. IV. Experimental results • Experiments : To compare compression rate of compounds, we obtained the number of abstracted compounds and edge crossings by applying two different layout algorithms: • Result 1 • Node compression rate performance • Scope • 1. 84 single metabolic pathways • 2. 8 major categorized metabolic pathways • 3. the global pathway • Result 2 • The number of edge crossing comparison between by • 1. Conventional algorithm • 2. Our Node abstraction featured scale-free layout algorithm Categorized pathways Global pathway … … single pathways IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

15. III. Experimental results Peripheral path as supplementary nodes Result 1B The Number of Nodes Before and After Applying Node Abstraction IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

16. III. Experimental results Peripheral path as super edges Result 1A Original Network Abstracted Network Results drawn with Cytoscape, using conventional spring embedding The red-colored edges represent the abstracted edges. (abstraction rate : 70%) IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

17. III. Experimental results Result 2 : Edge Crossing Reduction • In single metabolic pathways, the node abstraction featured algorithm reduced edge crossings by 63.31%. • In a global metabolic pathway, the number of edge crossings has reached a reduction of 58.08% in total. • Our proposed algorithm with node abstraction resulted in 86,067 edge crossings, whereas the one without node abstraction resulted in 205,316 edge crossings. IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

18. IV. Discussion • Two approaches were used: • 1. Abstracting compound pairs according to a consistent criteria • 2. Layout components according to high connectivity • Our experimental results show that node abstraction feature reduced the number of compounds by approximately 23% in global pathway. • Further discussion is necessary regarding enzyme reactions IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University

19. IV. Why is our work important? • The first systematic approach for Atlas visualization focusing on peripheral nodes • Fundamental to building a hierarchical structure of Atlas • Our approach is flexible upon pathway database change that frequently updates • It is a crucial preliminary step toward automatically drawn metabolic pathway • Future research on individual biological meaning of each peripheral nodes and abstracted path IEEE BIBM, 18-21 Dec 2010, Hong Kong EwhaWomans University