Splicing-site recognition of rice (Oryza sativa L.)DNA sequences

INTRODUCTIONCorrectlypinpointingsplicing sitesingenomicDNAsequencesisnotaneasytask ,whichisofgreatimportancetothegenomeannotationandgenefinding .Intronsaregenerallydividedinto3classes,namelycalssI,classIIandcommonnu cleuspre mRNA .IntronofclassIandIIcango…     

浅析如何提高初中生的写作水平

我们大家都知道,作文教学是语文课程的重要组成部份,在初中语文教学过程中,作文一直是学生的一大难题,相应的,学生作文水平一直不高,在教学中对教师而言,最难教的也是作文,针对这一“病症”,作为初中语文教师,我们如何才能激发学生的写作兴趣,从而提高差生的写作能力呢？本文结合自己多年教学经验浅析如下。     

Splicing-site recognition of rice (Oryza sativa L.)DNA sequences by support vector machines

Motivation: It was found that high accuracy splicing-site recognition of rice (Oryza sativa L.) DNA sequence is especially difficult. We described a new method for the splicing-site recognition of rice DNA sequences. Method: Based on the intron in eukaryotic organisms conforming to the principle of GT-AG, we used support vector machines (SVM) to predict the splicing sites. By machine learning, we built a model and used it to test the effect of the test data set of true and pseudo splicing sites. Results: The prediction accuracy we obtained was 87.53% at the true 5' end splicing site and 87.37% at the true 3' end splicing sites. The results suggested that the SVM approach could achieve higher accuracy than the previous approaches.