Bioinformatics of the sugarcane EST project

Telles, Guilherme P.; Braga, Marília D. V.; Dias, Zanoni; Tzy-Li, Lin; Quitzau, José Augusto Amgarten; Silva, Felipe Rodrigues da; Meidânis, João

doi:10.1590/s1415-47572001000100003

Cited by 27 publications

(10 citation statements)

References 9 publications

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“…The SUCEST database contains around 230,000 sequenced 5 ESTs (http://sucest.lad.ic.unicamp.br/en/; Telles et al, 2001) and we annotated 4,164 as belonging to the molecular chaperone category (Table I). This value Translated amino acid sequences of specifics mRNAs were chosen from chaperones and stress-related proteins deposited at public databases.…”

Section: Resultsmentioning

confidence: 99%

Molecular chaperone genes in the sugarcane expressed sequence database (SUCEST)

2001

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Some newly synthesized proteins require the assistance of molecular chaperones for their correct folding. Chaperones are also involved in the dissolution of protein aggregates making their study significant for both biotechnology and medicine and the identification of chaperones and stress-related protein sequences in different organisms is an important task. We used bioinformatic tools to investigate the information generated by the Sugarcane Expressed Sequence Tag (SUCEST) genome project in order to identify and annotate molecular chaperones. We considered that the SUCEST sequences belonged to this category of proteins when their E-values were lower than 1.0e-05. Our annotation shows that 4,164 of the 5' expressed sequence tag (EST) sequences were homologous to molecular chaperones, nearly 1.8% of all the 5' ESTs sequenced during the SUCEST project. About 43% of the chaperones which we found were Hsp70 chaperones and its co-chaperones, 10% were Hsp90 chaperones and 13% were peptidyl-prolyl cis, trans isomerase. Based on the annotation results we predicted 156 different chaperone gene subclasses in the sugarcane genome. Taken together, our results indicate that genes which encode chaperones were diverse and abundantly expressed in sugarcane cells, which emphasizes their biological importance.

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Section: Resultsmentioning

confidence: 99%

Molecular chaperone genes in the sugarcane expressed sequence database (SUCEST)

2001

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“…A total of 261,609 sequences have been grouped into 81,223 clusters based on an analysis with the phrap fragment assembly program. Results of comparisons between cluster consensus sequences and GenBank data were available for homology searches (Telles et al 2001).…”

Section: Sucest Database and Sequence Analysismentioning

confidence: 99%

Genomic distribution and characterization of EST-derived resistance gene analogs (RGAs) in sugarcane

et al. 2003

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A large sugarcane EST (expressed sequence tag) project recently gave us access to 261,609 EST sequences from sugarcane, assembled into 81,223 clusters. Among these, we identified 88 resistance gene analogs (RGAs) based on their homology to typical pathogen resistance genes, using a stringent BLAST search with a threshold e-value of e(-50). They included representatives of the three major groups of resistance genes with NBS/LRR, LRR or S/T KINASE domains. Fifty RGAs showed a total of 148 single-dose polymorphic RFLP markers, which could be located on the sugarcane reference genetic map (constructed in cultivar R570, 2n=approximately 115). Fifty-five SSR loci corresponding to 134 markers in R570 were also mapped to enable the classification of the various haplotypes into homology groups. Several RGA clusters were found. One cluster of two LRR-like loci mapped close to the only disease resistance gene known so far in sugarcane, which confers resistance to common rust. Detailed sequence comparison between two NBS/LRR RGA clusters in relation to their orthologs in rice and maize suggests their polyphyletic origins, and indicates that the degree of divergence between paralogous RGAs in sugarcane can be larger than that from an ortholog in a distant species.

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“…Unlike the classification tasks in which the variables are pre-defined, the clusterization needs, to identify automatically, the data groups, to which the researcher should attribute the variables (21)(22) . The most used algorithms in this task are the K-Means, KModes, KProtopypes, K-Medoids, Kohonem, among others (2,23) .…”

Section: Data Mining Tasksmentioning

confidence: 99%

Técnica de mineração de dados: uma revisão da literatura

Galvão

Marin

2009

Acta paul. enferm.

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The purpose of this study was to conduct a literature review on data mining (DM) technique in the LILACS and SciELO databases and specialized books. A broad data literature search using the words data mining (in English) and/or "mineração de dados" (in Portuguese) and limited to publications between 1999 and 2008, was conducted. The exclusion criteria were the keywords mining industry, mines, mineralogy, and publications that did not describe the methods and the tasks related to data mining. Of 123 publications retrieved, 38 were selected to review. Findings suggest that the existent amount of stored data is titanic and it continue to increase considerably. Thus, the process of knowledge discovery in databases and DM have developed tasks and methods for the retrieval of useful knowledge that may be of interest and necessary for just-in-time decision making in different areas of knowledge. Keywords: Information storage and retrieval/methods; Pattern recognition, automated/methods; Knowledge bases Medical Informatics RESUMOEste artigo teve como objetivo realizar uma revisão da literatura sobre a técnica de mineração de dados (Data Mining -DM) nas bases de dados abrangendo o Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), Scientific Eletronic Library Online (SCIELO) e alguns livros sobre o tema. Buscou-se uma coleta ampla utilizando as palavras data mining e mineração de dados, abrangendo o período de 1999 a 2008. Como critérios de exclusão foram utilizados os descritores: indústria mineira, minas, mineralogia; foram excluídos artigos que não esclareciam o método e as tarefas relacionadas à mineração de dados. Dos 123 artigos encontrados, 32 foram selecionados. Observou-se que o volume de dados armazenados é gigantesco e continua crescendo exponencialmente. Com isso o processo de Descoberta do Conhecimento em Bases de Dados e DM inclui tarefas e métodos para extração de conhecimento útil, interessante e indispensável na tomada de decisões rápidas nas mais diversas áreas de conhecimento. Descritores: Armazenamento e recuperação da informação/métodos; Reconhecimento automatizado de padrão/métodos; Bases de conhecimento; Informática médica RESUMENEn este artículo se tuvo como objetivo realizar una revisión de la literatura sobre la técnica de mineración de datos (Data Mining -DM) en las bases de datos que abarcaban la Literatura Latino-Americana y del Caribe en Ciencias de la Salud (LILACS), Scientific Eletronic Library Online (SCIELO) y algunos libros sobre el tema. Se buscó una recolección amplia utilizando las palabras data mining y mineración de datos, en el período comprendido entre 1999 a 2008. Como criterios de exclusión fueron utilizados los descriptores: industria minera, minas, mineralogía; se excluyeron artículos que no aclaraban el método y las tareas relacionadas a la mineración de dados. De los 123 artículos encontrados, 32 fueron seleccionados. Se observó que el volumen de datos almacenados es gigantesco y continúa creciendo exponencialmente. Con eso el proceso de Descubri...

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Bioinformatics of the sugarcane EST project

Cited by 27 publications

References 9 publications

Molecular chaperone genes in the sugarcane expressed sequence database (SUCEST)

Molecular chaperone genes in the sugarcane expressed sequence database (SUCEST)

Genomic distribution and characterization of EST-derived resistance gene analogs (RGAs) in sugarcane

Técnica de mineração de dados: uma revisão da literatura

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