We gratefully acknowledge support from the following agencies. For more information on specific research projects, please click on project titles with associated links.

National Resource for Network Biology
P41 RR031228
The National Resource for Network Biology will benefit public health by transforming large networks of molecular interactions into knowledge about the mechanisms of disease.  It will mine and visualize molecular networks to assemble quantitative and qualitative models of biological pathways and to use these models to predict patient outcomes. http://nrnb.org/

A systems approach to mapping the DNA damage response
R01 ES014811
The goal of this proposal is to elucidate the eukaryotic DNA damage response through an integrated experimental / computational approach leading to in-silico models of signaling and regulatory networks (Richard Kolodner, Co-I).

Cytoscape: A modeling platform for biomolecular networks
R01 GM070743
Cytoscape is an Open Source software project for integrating biomolecular interaction networks with genome-scale expression data and other molecular states into a unified conceptual framework. This grant provides funding for Cytoscape development efforts at UCSD and coordination activities among collaborators at Memorial Sloan-Kettering Cancer Center (MSKCC, Chris Sander, Co-I) and Institut Pasteur (Benno Schwikowski, Co-I).

Comparative physical and genetic interaction mapping in yeasts
R01 GM084279
This proposal is to generate high-density physical and genetic interaction maps in the model organism Schizosaccharomyces pombe and compare these to existing interaction maps of Saccharomyces cerevisiae.  All screens in Pombe will be targeted to a set of ~400 proteins covering the majority of kinases and DNA-binding transcription factors. 

Systems Biology Core of the Scripps NeuroAIDS Preclinical Studies (SNAPS)
P30 MH062261
The Scripps NeuroAIDS Preclinical Studies (SNAPS) is a multi-disciplinary center supporting biomedical research relevant to neurological AIDS.  This subcontract from Scripps aims to develop a suite of bioinformatics tools to help SNAPS scientists refine the extraction of pathway models from molecular interaction networks and better characterize their complex neuropathology.

III-CXT-Medium: Biological Data Integration Using Large-Scale Molecular Interaction Networks
IIS-0803937
This project will develop a protein-network-based approach to screen the gene expression profiles of patients from case-control studies, with the aim of achieving better diagnosis and molecular understanding of human disease.  The above funding amount reflects the direct costs that Ideker retains per year after funds are distributed to Richard Karp (coPI, UC Berkeley).

Pathway Association: A new paradigm for GWAS
Although genome-wide association studies (GWAS) are rapidly increasing in number, numerous challenges persist in identifying and explaining the associations between loci and quantitative phenotypes. This project is developing tools to integrate gene association data with protein network information to identify the pathways underlying a patient’s genotype.  These methods will elevate the study of gene association to a new study of “pathway association.”  The award is shared with Richard Karp in the EECS Department of UC Berkeley.

David and Lucille Packard Fellowship
The Packard Fellowship is awarded to “allow the nation’s most promising young professors to pursue science and engineering research with few funding restrictions and limited paperwork requirements.”  Ideker was one of 16 nominees chosen to receive a Packard award in 2004.

Network-based diagnostics for cancer
This grant from Pfizer supports a graduate student in the Ideker lab to develop methods for using protein-protein interaction networks in the diagnosis of cancer.  Individual mRNA biomarkers measured with microarray technology are clustered in the gene/protein network to identify pathways and modules whose aggregate (average) mRNA responses serve as predictive biomarkers.

Research in Systems Biology
This corporate grant provides funding for one software engineer to extend the Cytoscape platform (see above) to perform supervised clustering of gene expression profiles using protein interaction networks as input. The main target application is to map inflammatory and stress response pathways in human fibroblasts.