USA flag logo/image

An Official Website of the United States Government

DiseaseNet Finder: A Systems Medicine Toolkit for Clinical and Translational…

Award Information

Agency:
Department of Health and Human Services
Branch:
N/A
Award ID:
Program Year/Program:
2011 / SBIR
Agency Tracking Number:
R43RR031932
Solicitation Year:
2011
Solicitation Topic Code:
NCRR
Solicitation Number:
PAR09-220
Small Business Information
NEOPROTEOMICS, INC.
11000 CEDAR AVE, STE 100 CLEVELAND, OH 44106-3052
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2011
Title: DiseaseNet Finder: A Systems Medicine Toolkit for Clinical and Translational Rese
Agency: HHS
Contract: 1R43RR031932-01
Award Amount: $299,990.00
 

Abstract:

DESCRIPTION (provided by applicant): Many complex human diseases (e.g. cancer, diabetes, schizophrenia etc.) have correspondingly complex, polygenic genotypes that initiate and sustain disease progression. Despite significant progress over the past few decades identifying genes critical to mediating phenotype, our understanding of the functional basis of molecular phenotype for complex diseases is insufficient. Signaling pathways that consist of a few proteins interacting in a serial fashion oversimplify and provide inadequate models for the behavior mediated by multiple interacting gene products. Partly revealed by rigorous studies of increasingly well-annotated protein-protein interaction (PPI) networks, it has become clear that many of the proteins in these canonical signaling pathways engage in crosstalk with, and are modulated by, an ontologically diverse set of additional proteins, where this crosstalk is frequently mediated in a tissue and/or disease specific manner. We propose to develop and deliveran integrated suite of software tools to the academic and commercial research community to fulfill the unmet demand for quantitative PPI network analysis that can drive practical translational research and validation. The tool DiseaseNet Finder will search for and score candidate disease sub- networks within global PPI networks. It will permit integration of multiple high- dimensional -omic types (GWAS, SNP, CNV, proteomic, miRNA etc.) with PPI networks and include classification tools. Novel aspects of the software include: combinatorial scoring, multi data type integration, node and edge prediction tools, with end-point classification and quantitative scoring seamlessly implemented through graphical user interfaces. PUBLIC HEALTH RELEVANCE: Complex diseases include the contributions of many genes interacting with the environment. Enhanced computational research tools to discover biomarkers and understand complex disease mechanisms are needed to integrate the various types of genomic and proteomicsdata that are accumulating. This will permit a more rapid development of personalized medicine.

Principal Investigator:

Rod K. Nibbe
216-410-5181
rod.nibbe@neoproteomics.net

Business Contact:

John Schenkel
216-410-5181
john.schenkel@neoproteomics.net
Small Business Information at Submission:

NEOPROTEOMICS, INC.
11000 CEDAR AVE, STE 100 CLEVELAND, OH 44106-3052

EIN/Tax ID: 120434576
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No