Abstract
In the post-genomic era, gene function prediction get more and more attention. Splice site prediction is one of the most important part of those study. At present, a lot of algorithms have been proposed to this study, however, due to lack of understanding of the splicing mechanism, the performance of most of the methods has been influenced. This paper based on the relationship between the base and the codon designed a multi-scale algorithms for analysis of splice sites. In addition, the single nucleotide polymorphism has been used in this process, for exploration mutation on splicing mechanism by computation method. Finally, the experimental results showed that the proposed method can greatly improve the prediction accuracy. It is potentially interesting as an alternative tool in those studies.
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Acknowledgements
This study was supported by the Youth Fund for Humanities and Social Science Foundation of Ministry of Education of China (Grant No. 19XJC860006) and the National Natural Science Foundation of China (Grant No. 11974289/ A040506) and the Basic research plan of Natural Science in Shaanxi Province in 2021(Grant No. 2021JQ-878).
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Zhao, J., Wei, B., Niu, Y. (2023). Multi-scale Algorithm and SNP Based Splice Site Prediction. In: Xiong, N., Li, M., Li, K., Xiao, Z., Liao, L., Wang, L. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-031-20738-9_102
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DOI: https://doi.org/10.1007/978-3-031-20738-9_102
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