Erratum to: Splice site identification using probabilistic parameters and SVM classification
نویسندگان
چکیده
منابع مشابه
Hybrid Approach Using SVM and MM2 in Splice Site Junction Identification
Prediction of coding region from genomic DNA sequence is the foremost step in the quest of gene identification. In the eukaryotic organism, the gene structure consists of promoter, intron, start codon, exon and stop codon, etc. In the prediction of splice site, which is the separation between exons and introns, the accuracy is lower than 90% even when the sequences adjacent to the splice sites ...
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MOTIVATION Computational identification of functional sites in nucleotide sequences is at the core of many algorithms for the analysis of genomic data. This identification is based on the statistical parameters estimated from a training set. Often, because of the huge number of parameters, it is difficult to obtain consistent estimators. To simplify the estimation problem, one imposes independe...
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1 Introduction While more and more textual information is available online, effective retrieval is difficult without good indexing and summarization of documents content. Document categorization is one solution to this problem and is the task of classifying natural language documents into a set of predefined categories. A growing number of classification methods and machine learning techniques ...
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One major SVM weakness has been the use of generic kernel functions to compute distances among data points. Polynomial, linear, and Gaussian are typical examples. They do not take full advantage of the inherent probability distributions of the data. Focusing on audio speaker identification and verification, we propose to explore the use of novel kernel functions that take full advantage of good...
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Efficient family classification of newly discovered protein sequences is a central problem in bioinformatics. We present a new algorithm, using Probabilistic Suffix Trees, which identifies equivalences between the amino acids in different positions of a motif for each family. We also show that better classification can be achieved identifying representative fingerprints in the amino acid chains.
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2007
ISSN: 1471-2105
DOI: 10.1186/1471-2105-8-241