SBIR-STTR Award

Diseasenet Finder: a Systems Medicine Toolkit for Clinical and Translational Rese
Award last edited on: 4/12/16

Sponsored Program
SBIR
Awarding Agency
NIH : NCRR
Total Award Amount
$299,990
Award Phase
2
Solicitation Topic Code
-----

Principal Investigator
Rod K Nibbe

Company Information

NeoProteomics Inc (AKA: NEO PROTEOMICS INC)

11000 Cedar Avenue
Cleveland, OH 44106
   (216) 368-4268
   N/A
   www.neoproteomics.net
Location: Single
Congr. District: 11
County: 

Phase I

Contract Number: 1R43RR031932-01
Start Date: 3/15/11    Completed: 2/28/13
Phase I year
2011
Phase I Amount
$149,995
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 deliver an 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 proteomics data that are accumulating. This will permit a more rapid development of personalized medicine.

Thesaurus Terms:
Analysis, Data;Animal Model;Animal Models And Related Studies;Behavior;Benchmarking;Best Practice Analysis;Bio-Informatics;Bioinformatics;Biological;Biology;Body Tissues;Businesses;Cancers;Classification;Clinical;Clinical Research;Clinical Sciences;Clinical Study;Clinical Trials;Clinical Trials, Unspecified;Communities;Complex;Computational Science;Computer Programs;Computer Software Tools;Computer Software;Correlative Study;Data;Data Analyses;Development;Diabetes Mellitus;Disease;Disease Progression;Disorder;Drugs;Environment;Evaluation;Faculty;Gwas;Gene Expression;Genes;Genomics;Genotype;Goals;Graph;Graphical Interface;Human;Human, General;Internet;Investigators;Malignant Neoplasms;Malignant Tumor;Man (Taxonomy);Man, Modern;Mediating;Medication;Medicine;Micro Rna;Micrornas;Modeling;Mouse Protein;Ncrr;National Center For Research Resources;Network Analysis;Ohio;Outcome;Pathway Analysis;Pharmaceutic Preparations;Pharmaceutical Preparations;Phase;Phenotype;Plant Embryos;Programs (Pt);Programs [publication Type];Proteins;Proteomics;Research;Research Personnel;Researchers;Role;Sbir;Sbirs (R43/44);Scheme;Schizophrenia;Schizophrenic Disorders;Science Of Medicine;Seeds;Services;Signal Pathway;Small Business Innovation Research;Small Business Innovation Research Grant;Software;Software Tools;Staging;System;System, Loinc Axis 4;Systematics;Technology;Testing;Tissues;Tools, Software;Toxic Effect;Toxicities;Translational Research;Translational Research Enterprise;Translational Science;Universities;Validation;Www;Weight;Zygotes, Plant;Analytical Tool;Base;Biomarker;Clinical Investigation;Combinatorial;Commercialization;Community;Computer Program /Software;Computer Program/Software;Dementia Praecox;Diabetes;Disease /Disorder;Disease Phenotype;Disease/Disorder;Drug /Agent;Drug/Agent;Experience;Flexibility;Gene Product;Genome Wide Association Scan;Genome Wide Association Studies;Genome Wide Association Study;Genome-Wide Scan;Genomewide Association Scan;Genomewide Association Studies;Genomewide Association Study;Genomewide Scan;Graphic User Interface;Graphical User Interface;Human Disease;Improved;Innovate;Innovation;Innovative;Interest;Malignancy;Mirna;Model;Model Organism;Molecular Phenotype;Neoplasm /Cancer;Neoplasm/Cancer;Novel;Patient Population;Pre-Clinical;Preclinical;Programs;Protein Protein Interaction;Prototype;Schizophrenic;Seed;Social Role;Tool;Translation Research Enterprise;University;User-Friendly;Web;Whole Genome Association Studies;Whole Genome Association Study;World Wide Web

Phase II

Contract Number: 8R43GM103404-02
Start Date: 3/15/11    Completed: 8/28/13
Phase II year
2012
Phase II Amount
$149,995
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 deliver an 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 proteomics data that are accumulating. This will permit a more rapid development of personalized medicine.