PathwayOracle Toolkit |
Over decades of research, scientists and medical practitioners have provided incontrovertible evidence that cancer and many other devastating diseases originate in cells that have lost the ability to regulate their own behavior. Aberrations in both the cellular signaling network, responsible for controlling the cells response to external stimuli, and the gene transcription network, responsible for managing protein levels within the cell, have been implicated in numerous disease processes. As a result, the biological and medical research communities have committed themselves to gaining a better understanding of these networks and the mechanisms by which diseases develop in them.
The aim of the PathwayOracle project is to deliver a software system capable of rapidly testing experimental hypotheses and conducting other predictive analyses on cellular signaling networks. Unlike other approaches which require deeply parameterized models, PathwayOracle will provide biologists with accurate estimates of cellular behavior using a minimally detailed model. Such models can be constructed quickly and easily from biological literature and curated databases. As a result, our approach allows biologists to gain insights quickly into their signaling systems of interest
In the spirit of these goals, all of PathwayOracle's present and envisioned features require only the signaling network topology. We invite you to try PathwayOracle and hope that its capabilities deliver insights that will prove useful to your research.
As the software is under active development, we frequently add and update features. Please check back for new versions. If you have feedback, bug reports, or ideas for future features, please contact us.
This work was made possible in part through support from a Seed Grant awarded to Luay Nakhleh from the Gulf Coast Center for Computational Cancer Research, funded by John and Ann Doerr Fund for Computational Biomedicine, as well as by Grant Number R01CA125109 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.
If you use PathwayOracle in published research, please use the following citation for the tool:
D. Ruths, L. Nakhleh, and P. T. Ram. Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle. BMC Systems Biology, 2:76, 2008. (open access)
PathwayOracle is implemented in Python and is available in source form. It has the following dependencies which, depending on your platform, should be installed in two different ways.
Once these dependencies are installed, download the source distribution from here. Extract the source and follow instructions in the included README file.
If this is your first time using PathwayOracle, please take the introductory tutorial.
If you have published a paper that uses PathwayOracle, please let us know so we can add your publication to the collection of PathwayOracle literature.
Please contact Derek Ruths with feedback, questions, inquiries, and requests.
Our team is comprised of a collaboration between the Rice University Computer Science Department and the Systems Biology Department of MD Anderson:
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