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Nucleic Acids Research, 2001, Vol. 29, No. 1 102-105
© 2001 Oxford University Press

The Arabidopsis Information Resource (TAIR): a comprehensive database and web-based information retrieval, analysis, and visualization system for a model plant

Eva Huala1,*, Allan W. Dickerman2, Margarita Garcia-Hernandez1, Danforth Weems2, Leonore Reiser1, Frank LaFond2, David Hanley2, Donald Kiphart2, Mingzhe Zhuang2, Wen Huang1,2, Lukas A. Mueller1, Debika Bhattacharyya1, Devaki Bhaya1, Bruno W. Sobral2, William Beavis2, David W. Meinke3, Christopher D. Town4, Chris Somerville1 and Seung Yon Rhee1

1Carnegie Institution, Department of Plant Biology, 260 Panama Street, Stanford, CA 94305, USA, 2National Center for Genome Resources, 2935 Rodeo Park Drive East, Santa Fe, NM 87505, USA, 3Department of Botany, Oklahoma State University, Stillwater, OK 74078, USA and 4The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA

Arabidopsis thaliana, a small annual plant belonging to the mustard family, is the subject of study by an estimated 7000 researchers around the world. In addition to the large body of genetic, physiological and biochemical data gathered for this plant, it will be the first higher plant genome to be completely sequenced, with completion expected at the end of the year 2000. The sequencing effort has been coordinated by an international collaboration, the Arabidopsis Genome Initiative (AGI). The rationale for intensive investigation of Arabidopsis is that it is an excellent model for higher plants. In order to maximize use of the knowledge gained about this plant, there is a need for a comprehensive database and information retrieval and analysis system that will provide user-friendly access to Arabidopsis information. This paper describes the initial steps we have taken toward realizing these goals in a project called The Arabidopsis Information Resource (TAIR) (www.arabidopsis.org).

* To whom correspondence should be addressed. Tel: +1 650 325 1521; Fax: +1 650 325 6857; Email: huala{at}acoma.stanford.edu Present addresses: Allan W. Dickerman, Virginia Bioinformatics Institute (0477), 1750 Kraft Drive, Corporate Research Center Building 10, Suite 1400, Blacksburg, VA 24061, USA Donald Kiphart, Prediction Company, 236 Montezuma Avenue, Santa Fe, NM 87501, USA Mingzhe Zhuang, Sugen, Inc., 230 East Grand Avenue, South San Francisco, CA 94080-4811, USA


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