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A computational approach for prediction of donor splice sites with improved accuracy

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Title A computational approach for prediction of donor splice sites with improved accuracy
Not Available
 
Creator Prabina Kumar Meher
Tanmaya Kumar Sahu
A.R.Rao
S.D.Wah
 
Subject Machine learning
PreDOSS
Sequence encoding
Di-nucleotide dependency
Conditional error
 
Description Not Available
Identification of splice sites is important due to their key role in predicting the exon-intron structure of protein coding genes. Though several approaches have been developed for the prediction of splice sites, further improvement in the prediction accuracy will help predict gene structure more accurately. This paper presents a computational approach for prediction of donor splice sites with higher accuracy. In this approach, true and false splice sites were first encoded into numeric vectors and then used as input in artificial neural network (ANN), support vector machine (SVM) and random forest (RF) for prediction. ANN and SVM were found to perform equally and better than RF, while tested on HS3D and NN269 datasets. Further, the performance of ANN, SVM and RF were analyzed by using an independent test set of 50 genes and found that the prediction accuracy of ANN was higher than that of SVM and RF. All the predictors achieved higher accuracy while compared with the existing methods like NNsplice, MEM, MDD, WMM, MM1, FSPLICE, GeneID and ASSP, using the independent test set. We have also developed an online prediction server (PreDOSS) available at http://cabgrid.res.in:8080/predoss, for prediction of donor splice sites using the proposed approach.
Not Available
 
Date 2022-08-07T05:26:35Z
2022-08-07T05:26:35Z
2016-09-07
 
Type Research Paper
 
Identifier Prabina Kumar Meher, Tanmaya Kumar Sahu, A.R. Rao, S.D. Wahi, A (2016). computational approach for prediction of donor splice sites with improved accuracy, Journal of Theoretical Biology, 404, 285-294, ISSN 0022-5193,https://doi.org/10.1016/j.jtbi.2016.06.013.
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http://krishi.icar.gov.in/jspui/handle/123456789/73728
 
Language English
 
Relation Not Available;
 
Publisher Not Available