The immune system of higher organisms is, by any standard, complex. To date, using reductionist techniques, immunologists have elucidated many of the basic principles of how the immune system functions, yet our understanding is still far from complete.
In an era of high throughput measurements, it is already clear that the scientific knowledge we have accumulated has itself grown larger than our ability to cope with it, and thus it is increasingly important to develop bioinformatics tools with which to navigate the complexity of the information that is available to us.
ImmuneXpresso is an information extraction system, tailored for parsing the primary literature of immunology and relating it to experimental data.
The immune system is very much dependent on the interactions of various white blood cells with each other, either in synaptic contacts, at a distance using cytokines or chemokines, or both. Therefore, as a first approximation, ImmuneXpresso was used to create a literature derived network of interactions between cells and cytokines. Integration of cell-specific gene expression data facilitates cross-validation of cytokine mediated cell-cell interactions and suggests novel interactions.
Evaluation of the performance of this automatically generated multi-scale model against existing manually curated data shows that this system can be used to guide experimentalists in interpreting multi-scale experimental data.
Cite ImmuneXpresso (PubMed link): Towards a cytokine-cell interaction knowledgebase of the adaptive immune system. Shen-Orr SS, Goldberger O, Garten Y, Rosenberg-Hasson Y, Lovelace PA, Hirschberg DL, Altman RB, Davis MM, Butte AJ., Pac Symp Biocomput. 2009:439-50.
Get the ImmuneXpresso paper PDF from Stanford BMIR.
ImmuneXpresso project page on GForge.