Graph Modeling and Analysis in Oracle

Size: px

Start display at page:

Download "Graph Modeling and Analysis in Oracle"

Sophia Bradley
5 years ago
Views:

1 Graph Modeling and Analysis in Oracle Susie Stephens Principal Product Manager, Life Sciences Oracle Corporation BioPathways, July 30, 2004

2 Access Distributed Data UltraSearch External Sites Distributed query Flat files MySQL Sybase SRS External Tables Generic Connectivity DBlinks Transparent Gateway Transparent Gateway

3 Integrate Data Types H N N H O H N H O H N H H N H O S N O H XML

4 Manage Vast Quantities of Data Real Application Clusters Data Loads Protein data Chemistry Genome data High-speed interconnect

5 Enable Secure Collaboration LDAP User Management Virtual Private Database Selective Encryption Π Π Single Sign-On

6 Find Patterns and Insights 0101 ACTG Sequence Analysis Statistical Analysis Data & Text Mining OLAP & Reporting

7 Network Concept A network is a graph representation for modeling objects of interest and their relationships. It contains the following elements: Nodes: Links: Paths: objects of interests relationship between nodes ordered list of connected links X 0 X 1 k 2 S 1 k 1 X 0 S 1 X 2 k 3 S 1

8 NDM Architectural Goals Provide an open and generic data model for spatial and logical networks Separate application information from the network data model Simplify network data management Enable hierarchical modeling Support 2 tier or n-tier architecture

Framework for applying network constraints and rules Java

9 NDM Overview Data model for managing graph structures Rich graph analysis functions Supports variety of network structures Framework for applying network constraints and rules Java visualizer & APIs for 3 rd party application development Oracle Spatial option

10 Graph Analysis Functions Pathway Connectivity Shortest Path/All Paths Tracing (Accessibility) Within Distance Nearest Neighbor Minimum Bounding Rectangle Minimum Cost Spanning Tree

11 NDM Schema Network Metadata Name, Type, Node/Link/Path Table Information Network Tables Node Table Node_ID, Node_Type, Geometry, Link Table Link_ID, Link_Type, Start_Node_ID, End_Node_ID, Cost, Geometry, Path Table (Path-Link Table) Path_ID, Start_Node_ID, End_Node_ID, Cost, Geometry, Path Links, Application Information is added to network schema Add additional columns in node, link, and path tables directly Add foreign key(s) to node, link, and path tables

12 NDM APIs PL/SQL Package: (server-side) Network data query and management Maintains referential integrity and validation Supports link/node/path updates Java API: (mid-tier or client side) Network loading/storage Network analysis Network Creation/Editing Java Functional Extensibility Network, Node, Link, Path are Java Interfaces Application-based network analysis extensions

13 Metabolic Pathway Modeling Identify reaction paths between two given chemical compounds 1. Modeling Directed Network Chemical Compounds as Nodes Enzymes as Links Reaction Paths as Paths 2. Analysis Shortest Path Analysis All Path Analysis

14 Pathway Data Definition in NDM Node table NODE_ID NODE_NAME ACT COSTS SAMPLE_ID ENTRY_ID C00022 Y 1 Pyruvate 49 2 C00122 Y 1 Fumarate 50 3 C00036 Y 1 Oxaloacetate 51 4 C05379 Y 1 Oxalosuccinate 52 5 C00074 Y 1 Phosphoenolpyruvate 53 6 C00024 Y 1 Acetyl-CoA 54 7 C00149 Y 1 (S)-Malate 55 8 C00311 Y 1 Isocitrate 56 9 C00417 Y 1 cis-aconitate C00042 Y 1 Succinate 58 Link table LINK_ID LINK_NAME START_NODE_ID END_NODE_ID ACT COST SAMPLE_ID (rn:r00268) 4 19 Y 1 isocitrate dehydrogenase (NADP) (rn:r00268) 19 4 Y 1 isocitrate dehydrogenase (NADP) (rn:r00268) 4 20 Y 1 isocitrate dehydrogenase (NADP) (rn:r00268) 20 4 Y 1 isocitrate dehydrogenase (NADP) (rn:r00341) 3 19 Y 1 phosphoenolpyruvate carboxykinase (ATP) (rn:r00341) 3 5 Y 1 phosphoenolpyruvate carboxykinase (ATP) (rn:r00342) 3 7 Y 1 malate dehydrogenase (rn:r00344) 1 3 Y 1 pyruvate carboxylase Source: Susumu Goto, Kyoto University

15 Reference We are glad to hear that Oracle are developing the new Network Data Model specialized for the bioinformatics field. Efficient and effective pathway analysis will be achieved, especially for pathway computation from large amount of protein interaction and reaction data, using graph algorithms embedded in the model. - Professor and Director Minoru Kanehisa, Bioinformatics Center Institute for Chemical Research Kyoto University

16 Protein Interactions Infer functions of unknown proteins from their relationships with well-known proteins 1. Modeling Undirected Network Proteins as Nodes Interactions as Links 2. Analysis No. of Degrees (Neighboring Nodes) Shortest Path Analysis Within-Cost Analysis (Nearest Neighbor Analysis)

17 Reference "Oracle 10g's Network Data Model feature is great for building a semantic work infrastructure. Oracle 10g's graphical representation is an excellent tool for planning our Y2H protein interaction data storage needs and for building a signaling network from our Nature-AfCS Molecule Pages Database." - Joshua Li, Sr. Computational Scientist, San Diego Supercomputer Center / UCSD

18 Data Integration Integrate native biological databases by creating rules for network routes. Support multiple ontologies and jump in and out of database space for analysis 1. Modeling Directed Networks Classes as Nodes Interactions as Links 2. Analysis No. of Degrees (Neighboring Nodes) Shortest Path Analysis Within-Cost Analysis (Nearest Neighbor Analysis)

19 Integration Architecture Native Formats NREF EMBL GO KEGG BIND AFCS Distributed Database layer - Data type determines available routes - Routes can be determined using semantics Nodes Links Graph NDM layer (semantic layer) Network Route Source: Tom Plasterer, Beyond Genomics

Reference Oracle Database 10g's spatial network data model will assist in advancing our research and enable us to accelerate the drug discovery and development process.

20 Reference Oracle Database 10g's spatial network data model will assist in advancing our research and enable us to accelerate the drug discovery and development process. The incredible amount of research data we generate every day places unique challenges on our database. With integrated data manipulation and analytic tools, our scientists can be more efficient in processing and running computations. " - Aram Adourian, Ph.D., vice president, Computational Sciences, Beyond Genomics

21 Summary Oracle has functionality for: Distributed data access Integrating a variety of data types Managing vast quantities of data Enabling secure collaboration Finding patterns and insights NDM simplifies network management and analysis NDM will provide support for RDF by end of 2004 NDM takes advantage of the databases core functionality

Advances in Data Integration & Representation in Systems Biology

Advances in Data Integration & Representation in Systems Biology Susie Stephens Principal Product Manager, Life Sciences Oracle susie.stephens@oracle.com Outline Systems Biology Data Requirements Semantic