Pathway database models

Useful Resources and Webpages to Assemble Information on Kinetic Models, Including Pathway Databases and Model Repositories... 

Empath is a Cabinet database of metabolic pathways that models a metabolic pathway chart. It initially models the Boehringer Mannheim wall chart [35] but other pathway layouts are possible. It currently includes 1462 steps (metabolic reactions). The Empath database consists of more than 8000 live objects. Every object has an exact geometric location, that is, x, y coordinate, which is optionally indicated by visible hotspots. The chart is clickable everywhere and the image recenters itself around the selected point. The current object is the one closest to the center of the image and is identified by a bull s eye. A summary of the object is given (e.g., its structure, EC number, SMILES, reaction stoichiometry, etc.). Empath provides navigational features such as zoom in/out, wider, thinner, taller and shorter. 

Biologists have not only organized the cell into pathways and modules but also classified these pathways into various types. Each of the main types has a different computational representation in pathway databases. Bader and Enright (2005) discussed three biochemical- and biophysical-based pathways that are modeled ... 

ERGO Light Integrated Genomics Curated database of public and proprietary genomic DNA with connected similarities, functions, pathways, functional models, and clusters (http //www.ergo-light.com/)... 

Identifying constraints on reaction directions is essential for applications of metabolic flux analysis. However, in many applications the procedure used for determining reaction directions is not concretely defined. Typically, a subset of the reactions in a model is assigned as irreversible and the feasible directions are assigned based on information in pathway databases [59], In these applications, by treating certain reactions as implicitly unidirectional, biologically reasonable results can often be obtained without considering the system thermodynamics as outlined above. 

The analysis of network structure from the viewpoint of computer theory requires an introduction to some background information, which will be provided here. We will introduce the data involved for modeling metabolic pathways and the KEGG pathway database in particular. Furthermore, a basic introduction to graphs as used in computer science will be provided. 

A discussion of the mathematical and computational tools already available for the analysis of GRN models is given in the next section. Most of the models extracted from pathways databases are expected to be qualitative and incomplete in nature hence, the discussion focuses on qualitative network structures and how these structures influence the capacity of the system to exhibit certain dynamical behavior. 

FUN tool is a new integrated software based on a multimedia model, physiologically based pharmacokinetic (PBPK) models and associated databases. The tool is a dynamic integrated model and is capable of assessing the human exposure to chemical substances via multiple exposure pathways and the potential health risks (Fig. 9) [70]. 2-FUN tool has been developed in the framework of the European project called 2-FUN (Full-chain and UNcertainty Approaches for Assessing Health Risks in FUture ENvironmental Scenarios www.2-fun.org). 

SADA provides a full human health risk assessment module and associated databases. The risk models follow the USEPA s Risk Assessment Guidance for Superfund (RAGS) and can be customized to fit site-specific exposure conditions. It calculates risks based on the following exposure pathways ingestion, inhalation, dermal contact, food consumption, and also a combined exposure. 

Consider a molecular structure, which is the most important unifying information model in chemistry. Molecular structures appear in knowledgebases that represent catalogs of commercially available chemicals, pharmacology of named drugs, natural sources of bioactive molecules, protein-ligand interactions, measured molecular bioactivities, metabolic pathways, abstracted research literature, databases of synthetic reactions, and so on. 

This Accelrys provided database is based on the journals of the Royal Society of Chemistry (RSC) (308). It primarily contains information on the metabolic fate of chemicals (including pharmaceuticals, agrochemicals, food additives, and environmental and industrial chemicals) in vertebrates, invertebrates, and plants. New entries can be added, and the database may be searched graphically. This database can be combined with various computational tools from Accelrys for target-specific analysis and modeling. Metabolic pathways are organized alphanumerically, and future releases are scheduled to include a comprehensive survey of the metabolism literature (308,309). 

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