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University of Louisville Bioinformatics

Bioinformatics Research at the University of Louisville

Project:

MiDaR: Microarray Database Resource

Authors:

Eric C. Rouchka(1,3), Ravishrikanth Gundlapalli(1,3), Aun Munis(4), Nigel G.F. Cooper(2,3)

  1. University of Louisville Department of Computer Engineering and Computer Science.
  2. University of Louisville Department of Anatomical Sciences and Neurobiology.
  3. University of Louisville Department of Bioinformatics Research Group.
  4. University of Kentucky Department of Biology.
Motivation:
Microarray technology has the potential to yield a vast amount of gene expression data.  MiDaR is multifaceted project to explore the implementation of a database management and analysis resource for both custom microarrays (both cDNA and oligo based) and commercial microarrays (including Affymetrix and Agilent).  

The various aspects of MiDaR include:

Custom Chip Design
 (Gundlapalli, Rouchka and Cooper)
This part of the project deals with the physical layout of customized microarrays, allowing the user to determine which genes/gene groups to place on a given chip, as well as designing the oligos and/or primer products to represent each gene.  Each of these layouts can be stored in a database and edited at a later time.

Management of Microarray Data
(Hornsby, Jones, Rouchka, Brun, and Chang)
Object-relational database schemas for the management of microarray data from different sources is considered in the portion of MiDaR.  Data from different sources will be able to be interchanged for analysis purposes.

Relation of Microarray Data to Biological Information
(Jones, Brun, Rouchka, Johnson)
MiDaR will also allow the user to associate microarray information with other relevant genetic information, including related gene and protein structures, homologous sequences, and genetic regulatory pathways, both known and unknown.  This portion of MiDaR will potentially be tied into other sources of data as well, including proteomics and metabolomics.

Data Analysis
(Brun, Johnson, Rouchka, El-Hadik, Desoky, Elmaghraby)
The analysis of the differential expression of genes relative to a given cell type, stimulus, or time point is the most desired information for a biologist.  Portions of MiDaR are concerned with taking the data stored within the data management system, analyzing it, and placing the results of the experimental comparison back in the database.  The analysis are performed using customized routines connected with R, Bioconductor, and Matlab bioinformatics.

 
Results:
MiDaR is currently at the early phase of development for each of these modules.  More information will be made available as the project matures.

View the ISMB 2006 Poster


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