%0 Journal Article %1 Stoeckert:2001 %A Stoeckert, C. %A Pizarro, A. %A Manduchi, E. %A Gibson, M. %A Brunk, B. %A Crabtree, J. %A Schug, J. %A Shen-Orr, S. %A and G. C. Overton, %D 2001 %J Bioinformatics %K imported %N 4 %P 300--308 %T A relational schema for both array--based and SAGE gene expression experiments %U http://bioinformatics.oxfordjournals.org/cgi/content/abstract/17/4/300 %V 17 %X Motivation and Results: A relational schema is described for capturing highly parallel gene expression experiments using different technologies. This schema grew out of efforts to build a database for collaborators working on different biological systems and using different types of platforms in their gene expression experiments as well as different types of image quantification software. The tables are conceptually organized into three categories of information: Platform, Experiment (which includes image scanning and quantification), and Data. The strengths of the schema are: (i) integrating information on array elements using a gene index; (ii) describing samples using ontologies; (iii) reducing an experiment to a single RNA source for precise descriptions yet not losing the relationships between experiments done at the same time or for the same project; and (iv) maintaining both raw and processed (e.g. cleansed and normalized) data and recording how the data is processed. The result is a novel schema, which can hold both array and non-array data, is extensible for detailed experimental descriptions that are precise and consistent, and allows for meaningful comparisons of genes between experiments.

@article{Stoeckert:2001, abstract = {Motivation and Results: A relational schema is described for capturing highly parallel gene expression experiments using different technologies. This schema grew out of efforts to build a database for collaborators working on different biological systems and using different types of platforms in their gene expression experiments as well as different types of image quantification software. The tables are conceptually organized into three categories of information: Platform, Experiment (which includes image scanning and quantification), and Data. The strengths of the schema are: (i) integrating information on array elements using a gene index; (ii) describing samples using ontologies; (iii) reducing an experiment to a single RNA source for precise descriptions yet not losing the relationships between experiments done at the same time or for the same project; and (iv) maintaining both raw and processed (e.g. cleansed and normalized) data and recording how the data is processed. The result is a novel schema, which can hold both array and non-array data, is extensible for detailed experimental descriptions that are precise and consistent, and allows for meaningful comparisons of genes between experiments.}, added-at = {2007-10-23T13:35:30.000+0200}, author = {Stoeckert, C. and Pizarro, A. and Manduchi, E. and Gibson, M. and Brunk, B. and Crabtree, J. and Schug, J. and Shen-Orr, S. and and G. C. Overton}, biburl = {https://www.bibsonomy.org/bibtex/2acc05c6d38f402f9c4d770e3b7cbeb23/tkirsten}, interhash = {522e42882d1b54e0cf07cee380c66531}, intrahash = {acc05c6d38f402f9c4d770e3b7cbeb23}, journal = {Bioinformatics}, keywords = {imported}, number = 4, owner = {tkirsten}, pages = {300--308}, timestamp = {2007-10-23T13:35:41.000+0200}, title = {{A relational schema for both array--based and SAGE gene expression experiments}}, url = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/17/4/300}, volume = 17, year = 2001 }