Leishmania braziliensis: reanotação estruturação das informações em modelos de dados relacionais

• Ano de defesa: 2015
• Autor(a) principal: Torres, Felipe Guimarães
• Orientador(a): Queiróz, Artur Trancoso Lopo de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual de Feira de Santana
• Programa de Pós-Graduação: Mestrado em Computação Aplicada
• Departamento: DEPARTAMENTO DE CIÊNCIAS EXATAS
• País: Brasil
• Palavras-chave em Português: Leishmania braziliensis; Anotação genômica; Predição gênica; Banco de dados biológicos
• Palavras-chave em Inglês: Leishmania braziliensis; Genomic annotation; Bioinformatics; Genome prediction; Biological database
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://localhost:8080/tede/handle/tede/309

Cutaneous leishmaniasis affects 12 million people around the world. The main etiological agent in Brazil is Leishmania braziliensis. Its annotation is not very well characterized and have inaccurate regions because of the large number of hypothetical and putative genes. To solve this problem, we annotated the Leishmania braziliensis genome (MHOM / BR / 75 / M2904) with new algorithm and curated database by similarity. Initially, we downloaded these sequences of Leishmania braziliensis from NCBI and used GENSCAN and GLIMMER algorithms. We compared the predicted genes with SWISSPROT protein database. The comparison process was made by BLASTx and SWISS-PROT. We also used StructRNAFinder to predict the non-coding RNA, ncrna. We identified 25,539 ORF's, 4,916 genes, 735 ncRNA and 863 proteins. 94.75\% of predicted genes from Leishmania braziliensis were present on Leishmania panamensis genome (MHOM/PA/94/PSC-1). The comparison of ncrna number and proteins highlights a relation between chromosome and ncrna. All genes found were mapped and aligned to the Leishmania braziliensis genome and stored in a relational database model built in PHP 5.0 and MySQL. All data resulting of analyses in this work is available at www.leishdb.com.