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1.
Genet. mol. res. (Online) ; 6(1): 105-115, 2007. tab, ilus
Article in English | LILACS | ID: lil-456755

ABSTRACT

This paper presents a novel approach to the problem of splice site prediction, by applying stochastic grammar inference. We used four grammar inference algorithms to infer 1465 grammars, and used 10-fold cross-validation to select the best grammar for each algorithm. The corresponding grammars were embedded into a classifier and used to run splice site prediction and compare the results with those of NNSPLICE, the predictor used by the Genie gene finder. We indicate possible paths to improve this performance by using Sakakibara’s windowing technique to find probability thresholds that will lower false-positive predictions.


Subject(s)
Humans , Algorithms , Artificial Intelligence , Models, Molecular , RNA Splicing/genetics , Stochastic Processes
2.
Braz. j. med. biol. res ; 38(11): 1571-1574, Nov. 2005. ilus
Article in English | LILACS | ID: lil-414710

ABSTRACT

Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO) is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB.


Subject(s)
Humans , Sequence Analysis, DNA/methods , Computational Biology/instrumentation , Biomedical Research/instrumentation , Database Management Systems/instrumentation , Sequence Analysis, DNA/instrumentation , Databases, Genetic , Laboratories , Sequence Tagged Sites , User-Computer Interface
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