High Efficiency on Prediction of Translation Initiation Site (TIS) of RefSeq Sequences

Nobre, Cristiane Neri; Ortega, Josè Miguel; Braga, Antônio de Pádua

doi:10.1007/978-3-540-73731-5_13

Cited by 2 publications

(9 citation statements)

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“…), it was initially tested with the smaller databases, Mus musculus and Rattus Norvegicus , and then expanded to organisms which have a larger amount of mRNA: Arabidopsis thaliana , Caenorhabditis elegans , Drosophila melanogaster and Homo sapiens . All databases were extracted from the public database RefSeq [ 14 ] and relate to the organisms under the reviewed inspection level already evaluated by Nobre, Ortega and Braga [ 2 ].…”

Section: Methodsmentioning

confidence: 99%

“…Only part of the transcribed sequences carries information to codify proteins (CDS -CoDing Sequence). In other words, even though mRNA can be translated in its entirety, only a section of this mRNA is translated into amino acid [ 2 ]. Therefore, given a molecule of mRNA, a central problem of molecular biology is to determine whether it contains CDS and thereafter to discover which protein will be codified.…”

Section: Introductionmentioning

confidence: 99%

“…The lack of knowledge about the preservative features in the process of identifying the initiation of translation makes the prediction of the TIS a complex task. For this reason, computational methods which identify patterns can be used with the aim of extracting the implicit knowledge involved in this process [ 2 ]. Since 1982, the prediction of the TIS has been studied extensively using biological methods, statistics and computational techniques [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

“…Different computational methods have been applied to the prediction of the TIS including Artificial Neural Networks (ANN) [ 8 , 9 ], Support Vector Machines (SVM) [ 2 , 10 , 11 ] and the Gaussian Model [ 12 ]. Utilizing Artificial Neural Networks, Stormo et.…”

Section: Introductionmentioning

confidence: 99%

“…Nobre, Ortega and Braga [ 2 ] conducted experiments to discover the TIS using 12 nucleotides in the upstream and downstream regions, in addition to SVM with simple kernel functions. Inspired by a study conducted on the frequency of triplets of positive and negative sequences, they presented a new codification methodology.…”

Section: Introductionmentioning

confidence: 99%

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Improvement in the prediction of the translation initiation site through balancing methods, inclusion of acquired knowledge and addition of features to sequences of mRNA

et al. 2011

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BackgroundThe accurate prediction of the initiation of translation in sequences of mRNA is an important activity for genome annotation. However, obtaining an accurate prediction is not always a simple task and can be modeled as a problem of classification between positive sequences (protein codifiers) and negative sequences (non-codifiers). The problem is highly imbalanced because each molecule of mRNA has a unique translation initiation site and various others that are not initiators. Therefore, this study focuses on the problem from the perspective of balancing classes and we present an undersampling balancing method, M-clus, which is based on clustering. The method also adds features to sequences and improves the performance of the classifier through the inclusion of knowledge obtained by the model, called InAKnow.ResultsThrough this methodology, the measures of performance used (accuracy, sensitivity, specificity and adjusted accuracy) are greater than 93% for the Mus musculus and Rattus norvegicus organisms, and varied between 72.97% and 97.43% for the other organisms evaluated: Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Nasonia vitripennis. The precision increases significantly by 39% and 22.9% for Mus musculus and Rattus norvegicus, respectively, when the knowledge obtained by the model is included. For the other organisms, the precision increases by between 37.10% and 59.49%. The inclusion of certain features during training, for example, the presence of ATG in the upstream region of the Translation Initiation Site, improves the rate of sensitivity by approximately 7%. Using the M-Clus balancing method generates a significant increase in the rate of sensitivity from 51.39% to 91.55% (Mus musculus) and from 47.45% to 88.09% (Rattus norvegicus).ConclusionsIn order to solve the problem of TIS prediction, the results indicate that the methodology proposed in this work is adequate, particularly when using the concept of acquired knowledge which increased the accuracy in all databases evaluated.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%