Pathway building has been performed by individual groups studying a network of interest (e.g., immune signaling pathway) as well as by large bioinformatics consortia (e.g., the Reactome Project) and commercial entities (e.g., Ingenuity Systems). Pathway building is the process of identifying and integrating the entities, interactions, and associated annotations, and populating the knowledge base. Pathway construction can have either a data-driven objective (DDO) or a knowledge-driven objective (KDO). Data-driven pathway construction is used to generate relationship information of genes or proteins identified in a specific experiment such as a microarray study. Knowledge-driven pathway construction entails development of a detailed pathway knowledge base for particular domains of interest, such as a cell type, disease, or system. The curation process of a biological pathway entails identifying and structuring content, mining information manually and/or computationally, and assembling a knowledgebase using appropriate software tools. A schematic illustrating the major steps involved in the data-driven and knowledge-driven construction processes.
For either DDO or KDO pathway construction, the first step is to mine pertinent information from relevant information sources about the entities and interactions. The information retrieved is assembled using appropriate formats, information standards, and pathway building tools to obtain a pathway prototype. The pathway is further refined to include context-specific annotations such as species, cell/tissue type, or disease type. The pathway can then be verified by the domain experts and updated by the curators based on appropriate feedback. Recent attempts to improve knowledge integration have led to refined classifications of cellular entities, such as GO, and to the assembly of structured knowledge repositories. Data repositories, which contain information regarding sequence data, metabolism, signaling, reactions, and interactions are a major source of information for pathway building. A few useful databases are described in the following table.
Legend: Y – Yes, N – No; BIND – Biomolecular Interaction Network Database, DIP – Database of Interacting Proteins, GNPV – Genome Network Platform Viewer, HPRD = Human Protein Reference Database, MINT – Molecular Interaction database, MIPS – Munich Information center for Protein Sequences, UNIHI – Unified Human Interactome, OPHID – Online Predicted Human Interaction Database, EcoCyc – Encyclopaedia of E. Coli Genes and Metabolism, MetaCyc – aMetabolic Pathway database, KEGG – Kyoto Encyclopedia of Genes and Genomes, PANTHER – Protein Analysis Through Evolutionary Relationship database, STKE – Signal Transduction Knowledge Environment, PID – The Pathway Interaction Database, BioPP – Biological Pathway Publisher. A comprehensive list of resources can be found at http://www.pathguide.org.