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Bioinformatics of the Paracoccidioides brasiliensis EST Project
Marcelo M. Brígido1, Maria Emília M.T. Walter1, Adilton G. Oliveira1, Marcus K. Inoue1, Daniel S. Anjos1, Edans F.O. Sandes1, João J. Gondim1, Maria José de A. Carvalho1,
Nalvo F. Almeida Jr.2 and Maria Sueli Soares Felipe1
1Bioinformatics Laboratory, Department of Cellular Biology and
Department of Computer Science, University of Brasília, Brasília, DF, Brazil
2Department of Computing and Statistics, Federal University of Mato Grosso do Sul,
Campo Grande, MS, Brazil
Corresponding author: M.M. Brígido
E-mail: brigido@unb.br
Genet. Mol. Res. 4 (2): 203-215 (2005)
Received January 18, 2005
Accepted May 5, 2005
Published June 14, 2005

ABSTRACT. Paracoccidioides brasiliensis is the etiological agent of paracoccidioidomycosis, an endemic mycosis of Latin America. This fungus presents a dimorphic character; it grows as a mycelium at room temperature, but it is isolated as yeast from infected individuals. It is believed that the transition from mycelium to yeast is important for the infective process. The Functional and Differential Genome of Paracoccidioides brasiliensis Project - PbGenome Project was developed to study the infection process by analyzing expressed sequence tags - ESTs, isolated from both mycelial and yeast forms. The PbGenome Project was executed by a consortium that included 70 researchers (professors and students) from two sequencing laboratories of the midwest region of Brazil; this project produced 25,741 ESTs, 19,718 of which with sufficient quality to be analyzed. We describe the computational procedures used to receive process, analyze these ESTs, and help with their functional annotations; we also detail the services that were used for sequence data exploration. Various programs were compared for filtering and grouping the sequences, and they were adapted to a user-friendly interface. This system made the analysis of the differential transcriptome of P. brasiliensis possible.

Key words: Paracoccidioides brasiliensis, Differential transcriptome, Expressed sequence tags, Automatic annotation, Bioinformatics

 

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