Avaliação de Desempenho em Bioinformática: Estudo de caso de sistemas computacionais para a investigação de microRNAs
Abstract
This paper describe in details the computational evaluation of the miRQuest (http://mirquest.integrativebioinformatics.me/) system which is a webserver and middleware architecture integrating different standardized softwares for microRNA (miRNA) investigation.
References
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Barros-Carvalho GA, Paschoal AR, Marcelino-Guimarães FC, Hungria M. (2014) Prediction of potential novel microRNAs in soybean when in symbiosis. Genet Mol Res. 13(4):8519-29. doi: 10.4238/2014.October.20.28.
Brameier M, Wiuf C (2007). Ab initio identification of human microRNAs based on structure motifs. BMC Bioinformatics, 8:478.
Gomes CP1, Cho JH, Hood L, Franco OL, Pereira RW, Wang K. (2013) A Review of Computational Tools in microRNA Discovery. Front Genet. 15; 4:81. doi: 10.3389/fgene.2013.00081.
Janssen S. et. al. (2008). Shape based indexing for faster search of RNA family databases. BMC Bioinformatics, 9:131.
Jiang P. et. al. (2007). MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids, 35:339-344.
Kadri S. et al. (2009) HHMMiR: efficient de novo prediction of microRNAs using hierarchical hidden Markov models. BMC Bioinformatics. 10 Suppl 1:S35.
Kozomara A. and Griffiths-Jones S. (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. NAR 42: D68-D73
Lee RC, Feinbaum RL, Ambros V; Feinbaum; Ambros (1993). "The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14". Cell 75 (5): 843–54. Doi: 10.1016/0092-8674(93)90529-Y. PMID 8252621.
Machado-Lima, A.; del Portillo, H.A. ; DURHAM, A.M. (2008) Computational methods in noncoding RNA research. Journal of Mathematical Biology, v. 56, p. 15-49.
Oliveira KC, Carvalho MLP, Maracaja-Coutinho V, Kitajima JP, Verjovski-Almeida S (2011). Non-coding RNAs in schistosomes: an unexplored world. Anais da Academia Brasileira de Ciências, 83(2): 673-694.
Padilha IQM, Durbano JPM, Martins AB, Almeida RS, Maracaja-Coutinho V, Araújo DAM. (2008) A bioinformática como instrumento de inserção digital e difusão da biotecnologia. Revista Eletrônica Extensão Cidadã, 5.
Paschoal AR, Maracaja-Coutinho V, Setubal JC, Simões ZL, Verjovski-Almeida S, Durham AM. (2012) Non-coding transcription characterization and annotation: A guide and web resource for non-coding RNA databases. RNA BIOL, 9:274-282.
Powers, D. M.W. (2011) Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness e Correlation. Journal of Machine Learning Technologies, 2 (1) 37-63.
Severino P, Oliveira LS, Torres N, Andreghetto FM, Klingbeil Mde F, Moyses R, Wünsch-Filho V, Nunes FD, Mathor MB, Paschoal AR, Durham AM. (2013) High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research. BMC Genomics. 14:735. doi: 10.1186/1471-2164-14-735.
Steffen P. et al. (2006) RNAshapes: an integrated RNA analysis package based on abstract shapes. Bioinformatics. 22(4):500-3.
Taft RJ, Pheasant M, Mattick JS. (2007). The relationship between non-protein-coding DNA and eukaryotic complexity. Bioessays. 29(3):288-99.
Teune J.-H. and Steger, G. (2010) NOVOMIR: De Novo Prediction of MicroRNA-Coding Regions in a Single Plant-Genome. Journal of Nucleic Acids.
Xue C. et al. (2005) Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics, 6:310.
Zhang, B. et al. (2007) MicroRNAs and their regulatory roles in animals and plants. J. Cell. Physiol., 210:279–289.
Araújo DAM, Maracaja-Coutinho V, Padilha IQM, Rego TG. (2005) Genômica e Bioinformática: importância e perspectivas para o Nordeste. Ciência e Cotidiano. 1:5-9.
Barros-Carvalho GA, Paschoal AR, Marcelino-Guimarães FC, Hungria M. (2014) Prediction of potential novel microRNAs in soybean when in symbiosis. Genet Mol Res. 13(4):8519-29. doi: 10.4238/2014.October.20.28.
Brameier M, Wiuf C (2007). Ab initio identification of human microRNAs based on structure motifs. BMC Bioinformatics, 8:478.
Gomes CP1, Cho JH, Hood L, Franco OL, Pereira RW, Wang K. (2013) A Review of Computational Tools in microRNA Discovery. Front Genet. 15; 4:81. doi: 10.3389/fgene.2013.00081.
Janssen S. et. al. (2008). Shape based indexing for faster search of RNA family databases. BMC Bioinformatics, 9:131.
Jiang P. et. al. (2007). MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids, 35:339-344.
Kadri S. et al. (2009) HHMMiR: efficient de novo prediction of microRNAs using hierarchical hidden Markov models. BMC Bioinformatics. 10 Suppl 1:S35.
Kozomara A. and Griffiths-Jones S. (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. NAR 42: D68-D73
Lee RC, Feinbaum RL, Ambros V; Feinbaum; Ambros (1993). "The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14". Cell 75 (5): 843–54. Doi: 10.1016/0092-8674(93)90529-Y. PMID 8252621.
Machado-Lima, A.; del Portillo, H.A. ; DURHAM, A.M. (2008) Computational methods in noncoding RNA research. Journal of Mathematical Biology, v. 56, p. 15-49.
Oliveira KC, Carvalho MLP, Maracaja-Coutinho V, Kitajima JP, Verjovski-Almeida S (2011). Non-coding RNAs in schistosomes: an unexplored world. Anais da Academia Brasileira de Ciências, 83(2): 673-694.
Padilha IQM, Durbano JPM, Martins AB, Almeida RS, Maracaja-Coutinho V, Araújo DAM. (2008) A bioinformática como instrumento de inserção digital e difusão da biotecnologia. Revista Eletrônica Extensão Cidadã, 5.
Paschoal AR, Maracaja-Coutinho V, Setubal JC, Simões ZL, Verjovski-Almeida S, Durham AM. (2012) Non-coding transcription characterization and annotation: A guide and web resource for non-coding RNA databases. RNA BIOL, 9:274-282.
Powers, D. M.W. (2011) Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness e Correlation. Journal of Machine Learning Technologies, 2 (1) 37-63.
Severino P, Oliveira LS, Torres N, Andreghetto FM, Klingbeil Mde F, Moyses R, Wünsch-Filho V, Nunes FD, Mathor MB, Paschoal AR, Durham AM. (2013) High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research. BMC Genomics. 14:735. doi: 10.1186/1471-2164-14-735.
Steffen P. et al. (2006) RNAshapes: an integrated RNA analysis package based on abstract shapes. Bioinformatics. 22(4):500-3.
Taft RJ, Pheasant M, Mattick JS. (2007). The relationship between non-protein-coding DNA and eukaryotic complexity. Bioessays. 29(3):288-99.
Teune J.-H. and Steger, G. (2010) NOVOMIR: De Novo Prediction of MicroRNA-Coding Regions in a Single Plant-Genome. Journal of Nucleic Acids.
Xue C. et al. (2005) Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics, 6:310.
Zhang, B. et al. (2007) MicroRNAs and their regulatory roles in animals and plants. J. Cell. Physiol., 210:279–289.
Published
2015-07-20
How to Cite
AGUIAR, Rosana; AMBROSIO, Leandro; SEPÚLVEDA-HERMOSILLA, Gonzalo; MARACAJA-COUTINHO, Vinicius; PASCHOAL, Alexandre.
Avaliação de Desempenho em Bioinformática: Estudo de caso de sistemas computacionais para a investigação de microRNAs. In: WORKSHOP ON PERFORMANCE OF COMPUTER AND COMMUNICATION SYSTEMS (WPERFORMANCE), 14. , 2015, Recife.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 202-206.
ISSN 2595-6167.
DOI: https://doi.org/10.5753/wperformance.2015.10413.
