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Studies from University of Texas Yield New Data on Bioinformatics (CNCTDiscriminator: coding and noncoding transcript discriminator - an excursion...

July 15, 2014



Studies from University of Texas Yield New Data on Bioinformatics (CNCTDiscriminator: coding and noncoding transcript discriminator - an excursion through hypothesis learning and ensemble learning approaches)

By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Current study results on Bioinformatics have been published. According to news reporting originating in Arlington, Texas, by VerticalNews journalists, research stated, "The statistics about the open reading frames, the base compositions and the properties of the predicted secondary structures have potential to address the problem of discriminating coding and noncoding transcripts. Again, the Next Generation Sequencing platform, RNA-seq, provides us bounty of data from which expression profiles of the transcripts can be extracted which urged us adding a new set of dimension in this classification task."

The news reporters obtained a quote from the research from the University of Texas, "In this paper, we proposed CNCTDiscriminator --a coding and noncoding transcript discriminating system where we applied the integration of these four categories of features about the transcripts. The feature integration was done using both hypothesis learning and feature specific ensemble learning approaches. The CNCTDiscriminator model which was trained with composition and ORF features outperforms (precision 83.86%, recall 82.01%) other three popular methods --CPC (precision 98.31%, recall 25.95%), CPAT (precision 97.74%, recall 52.50%) and PORTRAIT (precision 84.37%, recall 73.2%) when applied to an independent benchmark dataset."

According to the news reporters, the research concluded: "However, the CNCTDiscriminator model that was trained using the ensemble approach shows comparable performance (precision 89.85%, recall 71."

For more information on this research see: CNCTDiscriminator: coding and noncoding transcript discriminator - an excursion through hypothesis learning and ensemble learning approaches. Journal of Bioinformatics and Computational Biology, 2013;11(5):1342002. Journal of Bioinformatics and Computational Biology can be contacted at: World Scientific Publishing Co. Pte. Ltd., 5 Toh Tuck Link, Singapore 596224. (World Scientific Publishing - www.worldscientific.com/; Journal of Bioinformatics and Computational Biology - www.worldscinet.com/jbcb/jbcb.shtml)

Our news correspondents report that additional information may be obtained by contacting A.K. Biswas, Computer Science and Engineering, The University of Texas at Arlington, Arlington, Texas 76019, United States. Additional authors for this research include B. Zhang, X. Wu and J.X Gao.

The publisher of the Journal of Bioinformatics and Computational Biology can be contacted at: World Scientific Publishing Co. Pte. Ltd., 5 Toh Tuck Link, Singapore 596224.

Keywords for this news article include: Texas, Arlington, United States, Bioinformatics, North and Central America.

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC


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Source: Information Technology Newsweekly


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