PathCase

Category Cross-Omics>Pathway Knowledge Bases/Databases/Tools and Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools

Abstract PathCase consists of three (3) different PathCase applications, under the umbrella of “PathCase”:

1) PathCase is an integrated software system for storing, managing, analyzing, and querying biological pathways at different levels of genetic, molecular, biochemical and organismal detail.

At the computational level, PathCase allows users to visualize pathways in multiple abstraction levels, and to pose predetermined as well as ad hoc queries using a graphical user interface.

Pathways are represented as graphs, and implemented as a relational database. PathCase has multiple levels, with multiple tools at each level.

The PathCase web client is a web-based interface to the PathCase Database, and provides a web-based toolset via a Java applet loaded within a browser window. It is designed as an intuitive and easy-to-use tool, with No need to study user manuals.

PathCase currently runs on one data set: PathCase featuring KEGG pathways.

PathCaseKEGG: This system features KEGG metabolic pathways. That is, it contains in its database, KEGG metabolic pathways. The KEGG data in the PathCaseKEGG database is refreshed every year, via a license from KEGG.

2) PathCase Systems Biology Workbench --

PathCaseSB System, currently being developed by a grant from NSF Biology, features PathCase Systems Biology Workbench that links metabolic pathways with systems biology models.

The aim of the PathCaseSB project is to build a framework and tools towards effective and efficient systems biology model development for multiscale mechanistic models of biological systems.

The manufacturer's approach is to integrate the model database with the manufacturer's metabolic network database PathCaseKEGG in order to build “one-shop” querying, visualization, simulation, and modeling capabilities.

While the PathCaseSB system is continually being improved and its database is being expanded, it currently has the following components:

PathCaseSB Database - The PathCaseSB Database contains systems biology models from BioModels [BioM] and metabolic pathways from KEGG [Kegg];

PathCaseSB Browser Interface - The PathCaseSB Browser Interface is a web-based interface that works with popular internet browsers.

Its goal is to provide a variety of browsing-based mechanisms for users to access the database, starting from a basic overview that lists the entities in the database to hierarchically drilled-down levels that is, among others, an advanced querying interface and visualization in the form of a graph.

The browser interface is built primarily for viewing the information related to:

PathCaseSB Visualization - PathCaseSB Visualization allows visualizations of pathways modeled by specific models as well as cross-reference visualizations between models and pathways. The visualization, made possible via the manufacturer's PathCase graph Viewer, allows for curated layouts for improved model visualization.

PathCaseSB Querying Interface - The PathCaseSB Querying Interface is designed to allow users to pose built-in (i.e., predefined) or ad hoc (i.e., constructed by the user during a query session as needed) queries involving models and pathways.

Currently, built-in queries, which can be characterized as a small set of queries that are the most popular ones by users, are implemented and available.

Note: Ad hoc queries are Not yet implemented.

PathCaseSB Simulation Interface - The PathCaseSB Simulation Interface uses SBML-specified systems biology models as input, and provides web-based (i.e., internet browser-based) model-simulation capabilities. It currently has two (2) simulation subsystems:

PathCaseSB Provenance Tool - The PathCaseSB Provenance Tool provides provenance information for the data in PathCaseSB database. Provenance is defined as “metadata that tracks the steps of data derivation, which can add value to the data itself”.

Since PathCaseSB System uses third party sources for most of its data (e.g., systems biology models from BioModels and metabolic pathways from KEGG), it is important for users to assess the trustworthiness of the data used in PathCaseSB.

For example, for a systems biology model, metadata information about a) the creators of the model, b) the publication that has lead to the model, and c) the references of the model are crucial about assessing the trustworthiness of the model.

The Provenance subsystem of PathCaseSB aims to provide support for storage, querying and visualization of provenance for the data used by the system. PathCaseSB specifies provenance data as a stand-alone panel. When a model is selected by the user, and the provenance panel is “clicked”, the provenance tool shows the provenance data about the selected model.

3) PathCase Metabolomics Analysis Workbench --

PathCaseMAW system, currently being developed by a grant from NSF Biology, features PathCase Metabolomics Analysis Workbench that is designed for metabolomics analysis.

Towards this end, PathCaseMAW database contains a fully hierarchically compartmentalized metabolic network for mammalians (humans and mice).

Full compartment hierarchy refers to the multi-tissue (e.g., liver, adipose tissue, muscle, etc.) environment as well as a complete biological compartment distinction (e.g., liver-cell, liver-cytosol, liver-mitochondrion, etc.). The network is being entered manually via an editor.

Recently, the manufacturers have developed three (3) frameworks for automated analysis of metabolomics data in terms of the dynamic behavior of the metabolic network:

1) Observed Metabolite Analysis (OMA) -- The Observed Metabolite Analysis (OMA) takes as input observed (measured) metabolite concentration increases and decreases within the metabolic network, and infers, as much as it can, those paths of reactions that “may” have increased and/or decreased fluxes in the metabolic network.

The idea of the OMA framework is to a) chase the implications of observed metabolite concentration increases and decreases within the metabolic network, and b) eliminate those metabolic network reaction paths with increased and/or decreased fluxes that could Not have happened, and c) return those metabolic network reaction paths (with increased and/or decreased fluxes) that may have happened.

The OMA framework does Not deal with the steady-state of the organism and does Not infer whether the reactions of the metabolic network are active or inactive at steady-state. The OMA Tool in PathCaseMAW is available and functional.

2) Metabolism Query Language (MQL -- The Metabolism Query Language (MQL) provides:

3) Steady-state Metabolic network Dynamics Analysis (SMDA) -- The Steady-state Metabolic network Dynamics Analysis (SMDA) reasons about the dynamic behavior of the metabolic network at steady-state, and locates possible alternatives for active/inactive metabolic subnetworks.

More specifically, SMDA a) assumes that the organism has reached a steady-state, and b) makes No assumptions about what the metabolite pool sizes are at the steady-state, or how the steady-state has been reached.

Given that a set of bio-fluid (e.g., blood) metabolite concentration values and, perhaps, a number of tissue-based metabolite concentration values are measured at steady-state, the question that is addressed by the SMDA framework is “what type of alternative steady-state metabolic network dynamic behavior scenarios exist, given the measurements?”

Currently, the SMDA framework is being implemented.

System Requirements

Contact manufacturer.

Manufacturer

Manufacturer Web Site PathCase

Price PathCase Licensing.

G6G Abstract Number 20104R

G6G Manufacturer Number 100490