CiteULike: Author Chervitz

Design and implementation of microarray gene expression markup language (MAGE-ML).

PT Spellman — 2004-11-22T00:17:30-00:00

Genome Biol, Vol. 3, No. 9. (23 August 2002)

BACKGROUND: Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies. RESULTS: To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems. CONCLUSIONS: MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.

SGD: Saccharomyces Genome Database.

JM Cherry — 2004-11-22T00:17:30-00:00

Nucleic Acids Res, Vol. 26, No. 1. (1 January 1998), pp. 73-79.

The Saccharomyces Genome Database (SGD) provides Internet access to the complete Saccharomyces cerevisiae genomic sequence, its genes and their products, the phenotypes of its mutants, and the literature supporting these data. The amount of information and the number of features provided by SGD have increased greatly following the release of the S.cerevisiae genomic sequence, which is currently the only complete sequence of a eukaryotic genome. SGD aids researchers by providing not only basic information, but also tools such as sequence similarity searching that lead to detailed information about features of the genome and relationships between genes. SGD presents information using a variety of user-friendly, dynamically created graphical displays illustrating physical, genetic and sequence feature maps. SGD can be accessed via the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/

Comparative genomics of the eukaryotes.

GM Rubin — 2005-04-18T15:09:18-00:00

Science, Vol. 287, No. 5461. (24 March 2000), pp. 2204-2215.

A comparative analysis of the genomes of Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae-and the proteins they are predicted to encode-was undertaken in the context of cellular, developmental, and evolutionary processes. The nonredundant protein sets of flies and worms are similar in size and are only twice that of yeast, but different gene families are expanded in each genome, and the multidomain proteins and signaling pathways of the fly and worm are far more complex than those of yeast. The fly has orthologs to 177 of the 289 human disease genes examined and provides the foundation for rapid analysis of some of the basic processes involved in human disease.

The Bioperl Toolkit: Perl Modules for the Life Sciences

Jason Stajich — 2005-11-30T16:53:45-00:00

Genome Res., Vol. 12, No. 10. (1 October 2002), pp. 1611-1618.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.[Supplemental material is available online at www.genome.org. Bioperl is available as open-source software free of charge and is licensed under the Perl Artistic License (http://www.perl.com/pub/a/language/misc/Artistic.html). It is available for download at http://www.bioperl.org. Support inquiries should be addressed to bioperl-l@bioperl.org.]

Submission of microarray data to public repositories.

CA Ball — 2007-11-24T23:41:54-00:00

PLoS Biol, Vol. 2, No. 9. (September 2004)

Comparison of the Complete Protein Sets of Worm and Yeast: Orthology and Divergence

Stephen Chervitz — 2007-11-10T19:19:20-00:00

Science, Vol. 282, No. 5396. (11 December 1998), pp. 2022-2028.

10.1126/science.282.5396.2022

An open letter on microarray data from the MGED Society.

C Ball — 2004-12-20T11:13:04-00:00

Microbiology, Vol. 150, No. Pt 11. (November 2004), pp. 3522-3524.