Bioinformatics expression databases

There are many products based on these life sciences standards, such as the aforementioned gene expression standard that is used in Rosetta Merck s Resolver product and the European Bioinformatics Institute s (EBI) Array-Express database. The LECIS (Laboratory Equipment Control Interface Specification) standard is used by Creon as part of their Q-DIS data standard support (note that one of the authors was the finalization task force chairperson for this standard). 

In this paper we describe the basic design of a microarray gene expression database to help microarray users and their informatics teams set up their information services. The first version of the microarray database object model ArrayExpress, which is described here, was developed at the European Bioinformatics Institute (EBI) in collaboration with the German Cancer Research Centre (DKFZ) and posted on the Internet in November, 1999 (see (http //www.ebi.ac.uk/arrayexpress)). A relational database implementation maxd based on the ArrayExpress object model was conducted at the University of Manchester (http //bioinf.man.ac.uk/microarray/resources.html) and is widely used for microarray laboratory informatics support. 

David, G. (2005) Covell Linking tumor cell cytotoxicity to mechanism of drug action An integrated analysis of gene expression, small-molecule screening and structural databases. Proteins Structure, Function, and Bioinformatics, 59 (3), 403-433. 

Large-scale gene expression studies, especially microarray technologies, have rapidly become a significant part of bioinformatics. There are many excellent sites focusing on microarray databases and tools for data analysis. The following sites are simply some examples. 

Facchiano A, A Weisz Internet tools for the analysis of gene expression by database integration, Proceedings of the NETTAB 2001 Workshop CORBA and XML—Toward a bioinformatics integrated network environment , Italy, 2001, pp. 99-102. 

The study of cellular protein expression by proteomics has relied on technologies that first appeared in the 1970s and have been continuously improved. In combination with advanced bioinformatics and large databases, proteomics now provide a powerful tool for basic research, clinical diagnostics, and drug development applications. 

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