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Abstract
DNA and RNA are two very important bio-molecules of the human cell. RNA is the second major form of nucleic acid in human cells that plays an intermediary role between DNA and functional protein. Several classes of RNA’s are found in cells, each with a / its distinct function. Understanding of storage and utilization of a cell’s genetic information is based on the structure of RNA. However, Many many experimental results have shown that RNA plays a another greater role in the cells. RNA sequences contains which contain signals at the structure level can be exploited to detect functional motifs common to all, or a portion of, those sequences. Different types of analysis of a structure can provide functional information in different degrees of detail. In this This paper discusses various types of RNA secondary structure representation has been discussed and in which appropriate structure has been adopted or ‘can be adopted’ if this is for the first time as appropriate for a probabilistic approach that shows un-ambiguity avoids ambiguity.
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References
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- DOWELL, R.D. and EDDY S.R. 2004. Evaluation of Several Lightweight Stochastic Context Free Grammars for RNA Secondary Structure Prediction. BMC Bioinformatics, 5: 71-78.
- HIROSHI, M., KENGO, S. and YASUBUMI S. 2005. Pair Stochastic Tree Adjoining Grammars for Yan, D. and Yulei, Z. 2005Aligning and Predicting Pseudoknot RNA Structures. Journal of Bioinformatics, 21: 2611-2617.
- HOPCROFT, J.E. and ULLMAN, J.D. 1979. Introduction to Automata Theory, Languages and Computation. Addison Wesley.
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- KEUM, Y.S. 2006. Recognition and Modeling of RNA Pseudoknots Using Context-Sensitive Pattern Matching. International Conference on Hybrid Information Technology (ICHIT), 2006.
- MOUNT, D.W. 2004. Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York USA.
- RAFAEL, G. 2006. Prediction of RNA Pseudoknotted Secondary Structure using Stochastic Context Free Grammars. CLEI Electronic Journal, 9(2): 221-228.
- ROBIN, D.D. and SEAN, R.E. 2006. Efficient Pairwise RNA Structure Prediction and Alignment Using Sequence Alignment Constraints. Journal of BMC Bioinformatics, 2006.
- SAAD, M. 2007. On the Approximation of Optimal Structures for RNA-RNA Interaction. IEEE Transactions on Computational Biology and Bioinformatics, 2007.
- SEARLS, D.B. 2002. The Language of Genes. Nature, 420: 211-217.
- WOODS, D.A. and BATZOGLOU, S. 2006. CONTRAfold: RNA Secondary Structure Prediction Without Physics-Based models. Bioinformatics 22(14): 90-98.
- YAN, D. and YULEI, Z. 2005. Statistical Parser For RNA Secondary Structure Prediction. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, 18-21 August 2005.
- YINGLEI, S. et. al. 2004. Tree Decomposition Based Fast Search of RNA Structures Including Pseudoknots in Genomes. Proceedings of IEEE Computational Systems Bioinformatics Conference, 2004.
- YUKI, K., HIROYUKI, S. and TADAO, K. 2003. A Comparative Study on Formal Grammars for Pseudoknots, Proceedings of Genome Informatics, 14: 470-471.
References
BYUNG-JUN, Y. and VAIDYANATHAN, P.P. 2007. Computational identification and analysis of noncoding RNAs. IEEE Signal Processing Magazine, 64-74.
DOWELL, R.D. and EDDY S.R. 2004. Evaluation of Several Lightweight Stochastic Context Free Grammars for RNA Secondary Structure Prediction. BMC Bioinformatics, 5: 71-78.
HIROSHI, M., KENGO, S. and YASUBUMI S. 2005. Pair Stochastic Tree Adjoining Grammars for Yan, D. and Yulei, Z. 2005Aligning and Predicting Pseudoknot RNA Structures. Journal of Bioinformatics, 21: 2611-2617.
HOPCROFT, J.E. and ULLMAN, J.D. 1979. Introduction to Automata Theory, Languages and Computation. Addison Wesley.
JIZHEN, Z., LIMING, C. and RUSSELL L.M. 2006. Learning the Parameters of Stochastic Grammar Models for RNA Structures with Pseudoknots. IEEE transactions, 170-175.
KEUM, Y.S. 2006. Recognition and Modeling of RNA Pseudoknots Using Context-Sensitive Pattern Matching. International Conference on Hybrid Information Technology (ICHIT), 2006.
MOUNT, D.W. 2004. Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York USA.
RAFAEL, G. 2006. Prediction of RNA Pseudoknotted Secondary Structure using Stochastic Context Free Grammars. CLEI Electronic Journal, 9(2): 221-228.
ROBIN, D.D. and SEAN, R.E. 2006. Efficient Pairwise RNA Structure Prediction and Alignment Using Sequence Alignment Constraints. Journal of BMC Bioinformatics, 2006.
SAAD, M. 2007. On the Approximation of Optimal Structures for RNA-RNA Interaction. IEEE Transactions on Computational Biology and Bioinformatics, 2007.
SEARLS, D.B. 2002. The Language of Genes. Nature, 420: 211-217.
WOODS, D.A. and BATZOGLOU, S. 2006. CONTRAfold: RNA Secondary Structure Prediction Without Physics-Based models. Bioinformatics 22(14): 90-98.
YAN, D. and YULEI, Z. 2005. Statistical Parser For RNA Secondary Structure Prediction. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, 18-21 August 2005.
YINGLEI, S. et. al. 2004. Tree Decomposition Based Fast Search of RNA Structures Including Pseudoknots in Genomes. Proceedings of IEEE Computational Systems Bioinformatics Conference, 2004.
YUKI, K., HIROYUKI, S. and TADAO, K. 2003. A Comparative Study on Formal Grammars for Pseudoknots, Proceedings of Genome Informatics, 14: 470-471.