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RISS 인기검색어
- 검색키워드
- 저자 : Rokeya Reaz, Mst. (검색결과 2 건)
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Survey on Nucleotide Encoding Techniques and SVM Kernel Design for Human Splice Site Prediction
Bari, A.T.M. Golam,Reaz, Mst. Rokeya,Choi, Ho-Jin,Jeong, Byeong-Soo Korean Society for Bioinformatics 2012 Interdisciplinary Bio Central (IBC) Vol.4 No.4
Splice site prediction in DNA sequence is a basic search problem for finding exon/intron and intron/exon boundaries. Removing introns and then joining the exons together forms the mRNA sequence. These sequences are the input of the translation process. It is a necessary step in the central dogma of molecular biology. The main task of splice site prediction is to find out the exact GT and AG ended sequences. Then it identifies the true and false GT and AG ended sequences among those candidate sequences. In this paper, we survey research works on splice site prediction based on support vector machine (SVM). The basic difference between these research works is nucleotide encoding technique and SVM kernel selection. Some methods encode the DNA sequence in a sparse way whereas others encode in a probabilistic manner. The encoded sequences serve as input of SVM. The task of SVM is to classify them using its learning model. The accuracy of classification largely depends on the proper kernel selection for sequence data as well as a selection of kernel parameter. We observe each encoding technique and classify them according to their similarity. Then we discuss about kernel and their parameter selection. Our survey paper provides a basic understanding of encoding approaches and proper kernel selection of SVM for splice site prediction.
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Codon-based encoding for DNA sequence analysis
Jeong, B.S.,Golam Bari, A.T.M.,Rokeya Reaz, Mst.,Jeon, S.,Lim, C.G.,Choi, H.J. Academic Press 2014 Methods Vol.67 No.3
With the exponential growth of biological sequence data (DNA or Protein Sequence), DNA sequence analysis has become an essential task for biologist to understand the features, functions, structures, and evolution of species. Encoding DNA sequences is an effective method to extract the features from DNA sequences. It is commonly used for visualizing DNA sequences and analyzing similarities/dissimilarities between different species or cells. Although there have been many encoding approaches proposed for DNA sequence analysis, we require more elegant approaches for higher accuracy. In this paper, we propose a noble encoding approach for measuring the degree of similarity/dissimilarity between different species. Our approach can preserve the physiochemical properties, positional information, and the codon usage bias of nucleotides. An extensive performance study shows that our approach provides higher accuracy than existing approaches in terms of the degree of similarity.
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