Biomedical subjects
Publications and source records attributed to John A Crow.
UNLABELLED: TableView is a generalized scientific visualization program for exploration of various biological data, including EST, SAGE, microarray and annotation data. Written in Java, TableView is portable, is easily used together with other software including DBMSs and is versatile enough to be applied to any tabular data AVAILABILITY: TableView is freely available at: http://ccgb.umn.edu/software/java/apps/TableView/.
In order to identify the genes and gene functions that underlie key aspects of legume biology, researchers have selected the cool season legume Medicago truncatula (Mt) as a model system for legume research. A set of >170 000 Mt ESTs has been assembled based on in-depth sampling from various developmental stages and pathogen-challenged tissues. MtDB is a relational database that integrates Mt transcriptome data and provides a wide range of user-defined data mining options. The database is interrogated through a series of interfaces with 58 options grouped into two filters. In addition, the user can select and compare unigene sets generated by different assemblers: Phrap, Cap3 and Cap4. Sequence identifiers from all public Mt sites (e.g. IDs from GenBank, CCGB, TIGR, NCGR, INRA) are fully cross-referenced to facilitate comparisons between different sites, and hypertext links to the appropriate database records are provided for all queries' results. MtDB's goal is to provide researchers with the means to quickly and independently identify sequences that match specific research interests based on user-defined criteria. The underlying database and query software have been designed for ease of updates and portability to other model organisms. Public access to the database is at http://www.medicago.org/MtDB.
As structural and functional genomics efforts provide the biological community with ever-broadening sets of interrelated data, the need to explore such complex information for subtle relationships expands. We present wCLUTO, a Web-enabled version of the stand-alone application CLUTO, designed to apply clustering methods to genomic information. Its first application is focused on the clustering transcriptome data from microarrays. Data can be uploaded by the user into the clustering tool, a choice of several clustering methods can be made and configured, and data are presented to the user in a variety of visual formats, including a three-dimensional "mountain" view of the clusters. Parameters can be explored to rapidly examine a variety of clustering results, and the resulting clusters can be downloaded either for manipulation by other programs or to be saved in a format for publication.