Sign-up for our newsletter
MAIN
Event Calendar
Awardee Reports
ABOUT DIACOMP
Citing DiaComp
Contact
Committees
Institutions
Awardee Reports
Publications
Bioinformatics
RESOURCES
Protocols & Methods
Reagents & Resources
Mouse Diet
Breeding Schemes
Validation Criteria
IMPC / KOMP Data
Publications
Bioinformatics
CONTACT
PARTICIPANT AREA
Login
▹
DiaComp Funded Abstracts
▹
Pilot & Feasibility
▹
Funding Programs
▹
Home
Pilot & Feasibility Program Application Abstract
A Centralized Data Mining and Analysis Portal for Diabetic Neuropathy Research
Eva Feldman
(Ann Arbor, MI)
Pilot & Feasibility Program
Diabetic neuropathy (DN) is the most common complication of diabetes with significant morbidity, mortality and cost. 60% - 70% of diabetic patients have neuropathy often resulting in poor quality of life. Better understanding of the molecular mechanism of development and progression of DN is crucial for designing mechanism based therapies. Genome-wide molecular studies in animal models are integral to understanding human disease pathogenesis. Diabetic Complications Consortium (DCC) has extensively characterized mouse models of human DN. Integrating high-throughput gene expression data in human DN with those in the animal models is critical in delineating species-specific as well as shared mechanisms between human and mouse. Our group has developed a database system that integrates transcriptomics data from our studies in mouse models and human DN. Goal of this proposal is to extend the existing system to form a centralized repository for publicly available transcriptomics data sets of DN and to provide a data-mining and data-analysis portal to the diabetes complications research community. Specific aims of the project are: Aim 1. Identify and annotate human and mouse DN gene expression data sets in the DCC data repository, National Center for Biotechnology Information (NCBI) Gene Expression Omnibus and European Bioinformatics Institute (EBI) ArrayExpress; process data using our established data processing pipeline to achieve consistency. Aim 2. Extend the existing database to efficiently store large transcriptomics data sets and upload processed data into the database; develop and implement data mining and data analysis tools with a user friendly web-based interface. Making this centralized data repository and analysis portal available to the research community at large will aid investigators in generating hypotheses and designing future experiments. Comparing gene regulation in the well characterized DCC murine models and human DN will facilitate selection of models that best recapitulate human disease mechanism for further exploration.
Welcome to the DiaComp Login / Account Request Page.
Email Address:
Password:
Note: Passwords are case-sensitive.
Please save my Email Address on this machine.
Not a member?
If you are a funded DiaComp investigator, a member of an investigator's lab,
or an External Scientific Panel member to the consortium, please
request an account.
Forgot your password?
Enter your Email Address and
click here.
ERROR!
There was a problem with the page:
User Info
User Confirm
Please acknowledge all posters, manuscripts or scientific materials that were generated in part or whole using funds from the Diabetic Complications Consortium(DiaComp) using the following text:
Financial support for this work provided by the NIDDK Diabetic Complications Consortium (RRID:SCR_001415, www.diacomp.org), grants DK076169 and DK115255
Citation text and image have been copied to your clipboard. You may now paste them into your document. Thank you!