The impact of environmental exposures on human health can be investigated using cDNA microarray technology to determine the effects of environmental challenges on the pattern of gene expression. The ability to analyze and compare various patterns of gene transcription is of interest to assign gene expression profiles to various disease states. The ability to integrate access to such a wide variety of public biological resources with that of comparative gene expression data, is of value to critically manage, analyze, and interpret intrinsic gene expression profiles. Very few systems are available that integrate gene expression data with public biological information.
Commercial systems are costly and require customizations to implement.
The advancements in information technology and expanding application development provide the ability to design data management and analysis systems that not only warehouse information, but facilitate relational integration and interpretation of large-scaled microarray gene expression data with outputs from multiple distributed biological resources. The schema above illustrates a typical architecture designed to provide seamless user access to distributed databases and biological resources. The interface abstraction layer encapsulates API mediator and database module specifications that channel client requests to specific database servers and trigger generic SQL queries. Data sets are readily accessed and manipulated on the fly without stored procedures, subprograms, or platform specific calls. Embedding statistical algorithms or commercial data analysis software into the infrastructure can further customize the system.