Pathway Related Data Models

A number of groups (many of them participants in BioPAX) have data models to represent pathway information. This page is a place to collect whatever detailed documention on the model, schema, and definitions we can get on these models so we can study and learn from them. Databases will be listed in alphabetic order.

aMAZE is a Workbench for the representation, management, annotation and analysis of information on networks of cellular processes: genetic regulation, biochemical pathways, signal transductions.
 * attachment:amaze.owl
 * attachment:amaze.pprj
 * attachment:amaze_conceptual.pdf

BIND The Biomolecular Interaction Network Database (BIND) is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature.
 * BIND Curation Guide
 * BIND asn specification

CellML The purpose of CellML is to store and exchange computer-based mathematical models. Although CellML was originally intended for the description of biological models, it has a broader application. CellML includes information about model structure (how the parts of a model are organizationally related to one another), mathematics (equations describing the underlying processes) and metadata (additional information about the model that allows scientists to search for specific models or model components in a database or other repository).
 * Specification
 * Sample models

INOH (Integrating Network Objects with Hierarchies) is a pathway database of model organisms including human, mouse, rat and others. In INOH, the term pathway refers to higher order functional knowledge such as relationships among multiple bio-molecules that constitute signal transduction pathways or biological events in general.
 * RREX: a query interface for biological processes with hierarchical and recursive structures (a little old)
 * Knowledge representation of signal transduction pathways (first paper that formalised pathway hierarchy as a compound graph)
 * The molecule role ontology: an ontology for annotation of signal transduction pathway molecules in the scientific literature In INOH, every pathway object is annotated by a GO-like ontology (DAG structured CV). For example, generic-ness/concrete-ness of a protein or a biological process is defined by their ontological annotation.
 * The DAG-structured CVs Browse CVs described above
 * Event Ontology
 * Molecular Role Ontology

PSI-MI The PSI Molecular Interaction work group developed and maintains a common data standard that will allow users to retrieve all relevant data from different sites and perform comparative analysis of different data sets much more easily than is currently possible. The standard defines a minimal data model that allows scientists to provide core data, but refer back to the original data source for full information, in particular for complex, fully curated entries.
 * OBO format[[FootNote(OBO is the Open Biomedical Ontologies)]]
 * XML schema

Reactome is a curated database of biological processes in humans. It covers biological pathways ranging from the basic processes of metabolism to high-level processes such as hormonal signalling. While Reactome is targeted at human pathways, it also includes many individual biochemical reactions from non-human systems such as rat, mouse, fugu fish and zebra fish. This makes the database relevant to the large number of researchers who work on model organisms. All the information in Reactome is backed up by its provenance: either a literature citation or an electronic inference based on sequence similarity. *Data model overview *Schema browser

ResNet is an XML-based format designed to describe molecular networks and cellular pathways. Each block in XML file represents a mini-network described in a single sentence.
 * Specification (section 1.7 onwards)

The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biochemical reaction networks. SBML is applicable to metabolic networks, cell-signaling pathways, regulatory networks, and many others.
 * [attachment:sbml-level-2-v1.pdf Specification]
 * XML schema
 * EFGR pathway represented in SMBL from A comprehensive pathway map of epidermal growth factor receptor signaling.

Patika An ontology to model networks of cellular processes through integration of information on individual pathways. The ontology is suitable for modeling incomplete information and abstractions of varying levels for complexity management.
 * An ontology for collaborative construction and analysis of cellular pathways describes the ontology.

Systems Biology Markup Language (SBGN) is a graphical notation for representing biological interactions. The goal of SBGN is to be the standard way of graphically representing various biological interactions in a well-defined way.
 * The Process Diagram: Rational and Definition

ROSPath is designed to describe cellular signaling processes in molecular detail and to accumulate data and knowledge regarding signaling pathways in an organized database structure.
 * Multi-layered Representation for Cell Signaling Pathways

The KEGG Markup Language (KGML) is an exchange format of the KEGG graph objects, especially the KEGG pathway maps that are manually drawn and updated. KGML enables automatic drawing of KEGG pathways and provides facilities for computational analysis and modeling of protein networks and chemical networks.
 * KEGG XML

UniPath: A Knowledge Representation System for Biological Pathways

Cell Signaling Networks Ontology: Although databases for cell signaling pathways include numbers of reaction data of the pathways, the reaction data cannot be used yet to deduce biological functions from them. For the deduction, we need systematic and consistent interpretation of biological functions of reactions in cell signaling pathways in the context of "information transmission". To address this issue, we have developed a functional ontology for cell signaling pathways, Cell Signaling Network Ontology (CSN-Ontology), which provides framework for the functional interpretation presenting some important concepts as information, selectivity, movability, and signaling rules including passage of time.
 * Ontology based standardization of Petri net modeling for signaling pathways
 * Ontological Integration of Data Models for Cell Signaling Pathways by Defining a Factor of Causality Called ‘Signal’