Research Support

The Ideker Lab gratefully acknowledges active research support from the following agencies. For more information on specific research projects, please click on project titles with associated links.


The Cancer Cell Map Initiative (CCMI)
NIH / NCI U54 CA209891
Krogan, Ideker (MPI)
The CCMI seeks to enable a new paradigm in cancer discovery and treatment based on experimental elucidation of protein and genetic networks underlying cancer. Ideker co-directs this center with Dr. Nevan Krogan at UCSF. Ideker is supported to experimentally generate and analyze genetic (synthetic-lethal) interaction maps across head-and-neck and breast cancer cell lines. CCMI is an NCI Cancer Systems Biology Center (CSBC).


The Psychiatric Cell Map Initiative (PCMI)
NIH / NIMH U01 MH115747
Willsey, Krogan, Kampmann, Ideker (MPI)   
The Psychiatric Cell Map Initiative (PCMI) seeks to bridge the gap between the genome and clinic in the field of neuropsychiatric disorder research by mapping the physical and genetic interaction networks underlying diseases like autism, epilepsy, and schizophrenia. Ideker is one of four multiple PIs of this center and oversees a bioinformatics project to analyze center-generated network data.


The Host Pathogen Mapping Initiative (HPMI)
NIH / NIAID U19 AI135990
Krogan (PI); Ideker (Co-Lead/Co-I)
The mission of the Host-Pathogen Map Initiative (HPMI) is to understand how host cells respond to invasive microbes and identify the mechanisms by which pathogens thwart natural immunity. HPMI will apply systematic approaches to comprehensively identify the common molecular networks that underlie pathogenesis and will use these maps as key resources for novel therapies.

NIGMS
Cytoscape: A modeling platform for biomolecular networks
NIH / NHGRI R01 HG009979
Ideker (PI); Bader (Co-I)
Cytoscape is an Open Source bioinformatics software environment for biological network analysis and modeling. This award funds continued development and maintenance of the existing functionality of Cytoscape with expanded support for human genetic analysis and analysis of gene expression. Ideker collaborates in this work with Co-I Gary Bader’s lab at University of Toronto.


NDEx – The Network Data Exchange a Network Commons for Biologists
NIH / NCI U24 CA184427
Ideker (PI)     
The Network Data Exchange (NDEx) is a collaborative web resource that captures knowledge of the structure and function of molecular networks giving rise to cancer. This system is comprised of (1) a freely available, open-source server platform and (2) a public website built on that platform. Researchers use NDEx to access, share, and publish biological knowledge in multiple network formats.

NIGMS
National Resource for Network Biology (NRNB)
NIH / NIGMS P41 GM103504
Ideker (PI); (Multiple Co-Is) 
NRNB is a Biomedical Technology Research Resource (BTRR) funded by NIGMS. It aims to provide open-source software that broadly enables network-based analysis and biomedical discovery for NIH-funded researchers. Ideker directs this resource and supervises research and development activities related to detection of hierarchical network structure and network-guided predictive models.

NIEHS
A systems approach to mapping the DNA damage response
NIH / NIEHS - R01ES014811
Ideker (PI); Sobol (Co-I)
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.  These studies are performed in collaboration with the laboratory of Co-I Robert Sobol at University of Alabama.


Regulation of Postsynaptic Protein Interaction Networks in Complex Brain Disorders
NIH / NIMH  R01 MH115005
Coba (PI); Ideker (Co-I)
The goals of this research program are to determine how mutations associated with schizophrenia disrupt protein interaction networks at the post-synaptic density, increasing our understanding of how disease risk factors are functionally organized in protein networks. Ideker supervises a part-time bioinformatics scientist to analyze protein networks experimentally generated by PI Marcelo Coba at the University of Southern California.


Biomedical Data Translator Technical Feasibility Assessment and Architecture Design
NIN / NCATS OT3 TR002026 
Huang (PI); Ideker (Project Leader)
The Ideker laboratory is an active participant in the NCATS Data Translator Project, as part of Team Blue led by Dr. Sui Huang of the Institute for Systems Biology (http://ncats.nih.gov/translator/projects). The goal is to design and prototype a strategy for biomedical data translation we call DeepTranslate, working in collaboration with many other teams nationwide.



Recently Completed Support 


Ideker (PI)
The San Diego Center for Systems Biology is a cross cutting initiative directed by Trey Ideker and involving investigators from UCSD, Salk, Scripps, and the Sanford/Burnham Institute.  Ideker is leading a genetic interaction-mapping project on stress responses in yeast, and he is also running the Bioinformatics Core, which provides broad bioinformatics support to dozens of Center investigators.


NIGMS
Comparative physical and genetic interaction mapping in yeasts
NIGMS R01 GM084279
Ideker; Krogan (Multiple Co-Is)
This grant funds work to generate high-density physical interaction maps (protein-DNA, protein-protein) and genetic interaction maps (synthetic lethals and epistasis) in the model organism Schizosaccharomyces pombe. These network data are providing a major resource for evolutionary comparison to existing interaction maps of Saccharomyces cerevisiae.  This proposal is jointly directed by Ideker and his collaborator, Nevan Krogan, at UCSF.

 

Novel paradigms in diabetic complications
NIDDK DP3 DK094352
Sharma (PI); Ideker (Co-I)
Diabetic kidney disease is recognized as the leading cause of excess mortality in the population with type 1 diabetes. Using a systems biology and imaging approach we will link the reduction in mitochondrial function with alterations in the metabolome and epigenome in the kidney and the urine. This application will be a paradigm shifting approach to the medical challenge of hyperglycemia induced kidney disease.