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  Phytophthora Database: A Forensic Database Supporting the Identification and Monitoring of Phytophthora  
 
 
  Authours
 Jongsun Park*, Bongsoo Park*, Narayanan Veeraraghavan*, Kyongyong Jung, Yong-Hwan Lee, Jaime E. Blair, David M. Geiser, Scott Isard, Michele A. Mansfield, Ekaterina Nikolaeva, Sook-Young Park, Joseph Russo, Seong H. Kim, Matthew Greene, Kelly L. Ivors, Yilmaz Balci, Masoomeh Peiman, Donald C. Erwin, Michael D. Coffey, Amy Rossman, David Farr, Erica Cline, Niklaus J. Grünwald, Douglas G. Luster, Julia Schrandt, Frank Martin, Olaf K. Ribeiro, Izabela Makalowska, and Seogchan Kang
  Title  Phytophthora Database: A Forensic Database Supporting the Identification and Monitoring of Phytophthora
  Journal  Plant Disease, 2008 (92) ~
  Abstract
 Phytophthora species represent a serious threat to agricultural and ecological systems. Many novel Phytophthora species have been reported in recent years, which is indicative of our limited understanding of the ecology and diversity of Phytophthora in nature. Systematic cataloging of genotypic and phenotypic information on isolates of previously described species serves as a baseline for identification, classification, and risk assessment of new Phytophthora isolates. The Phytophthora Database (PD) was established to catalog such data in a web-accessible and searchable format. To support the identification of new Phytophthora isolates via comparison of their sequences at one or more loci with the corresponding sequences derived from the isolates archived in the PD, we generated and deposited sequence data from more than 1,500 isolates representing the known diversity in the genus. Data search and analysis tools in the PD include BLAST, Phyloviewer (a program for building phylogenetic trees using sequences of selected isolates), and Virtual Gel (a program for generating expected restriction patterns for given sequences). The PD also provides a customized means of storing and sharing data via the web. The PD serves as a model that can be easily adopted to develop databases for other important pathogen groups.
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  Department of Agricultural Biotechnology, Seoul National University, Korea
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