An Algorithm to Classify Amino Acid Sequences into Protein Groups of Bothrops jararacussu Venomous Gland

Author(s): Silvana Giuliatti, Milton Faria Jr., Fernando Camargo, Luiz Paulo Camargo, Suzelei C. Franca, Andreimar M. Soares

Journal Name: Protein & Peptide Letters

Volume 12 , Issue 4 , 2005

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An algorithm for automatic clustering of database protein sequences from Bothrops jararacussu venomous gland, according to sequence similarities of their domains, is described. The program was written in C and Perl languages. This algorithm compares a domain with each ORF protein sequence in the database. Each nucleotide FASTA sequence generates six ORFs. As a result, the user has a list containing all sequences found in a specific domain and a display of the sequence, domain and number of hits. The algorithm lists only the sequences that present a minimum similarity of 30 hits and the best alignment. This limit was considered appropriate. The algorithm is available in the Internet ( and it can quickly and accurately organizes large database into classes.

Keywords: proteins, snake venom, bothrops jararacussu, bioinformatic, algorithm

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Article Details

Year: 2005
Page: [333 - 337]
Pages: 5
DOI: 10.2174/0929866053765680
Price: $65

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