» Articles » PMID: 34790508

Improved Recognition of Splice Sites in by Incorporating Secondary Structure Information into Sequence-derived Features: a Computational Study

Overview
Journal 3 Biotech
Publisher Springer
Specialty Biotechnology
Date 2021 Nov 18
PMID 34790508
Citations 1
Authors
Affiliations
Soon will be listed here.
Abstract

Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-021-03036-8.

Citing Articles

ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with Pseudo -Tuple Nucleotide Compositional Features.

Meher P, Begam S, Sahu T, Gupta A, Kumar A, Kumar U Int J Mol Sci. 2022; 23(3).

PMID: 35163534 PMC: 8835813. DOI: 10.3390/ijms23031612.

References
1.
Meher P, Sahu T, Rao A, Wahi S . A computational approach for prediction of donor splice sites with improved accuracy. J Theor Biol. 2016; 404:285-294. DOI: 10.1016/j.jtbi.2016.06.013. View

2.
Rogic S, Montpetit B, Hoos H, Mackworth A, Ouellette B, Hieter P . Correlation between the secondary structure of pre-mRNA introns and the efficiency of splicing in Saccharomyces cerevisiae. BMC Genomics. 2008; 9:355. PMC: 2536676. DOI: 10.1186/1471-2164-9-355. View

3.
Baten A, Chang B, Halgamuge S, Li J . Splice site identification using probabilistic parameters and SVM classification. BMC Bioinformatics. 2007; 7 Suppl 5:S15. PMC: 1764471. DOI: 10.1186/1471-2105-7-S5-S15. View

4.
Li J, Wang L, Wang H, Bai L, Yuan Z . High-accuracy splice site prediction based on sequence component and position features. Genet Mol Res. 2012; 11(3):3432-51. DOI: 10.4238/2012.September.25.12. View

5.
Hofacker I . Vienna RNA secondary structure server. Nucleic Acids Res. 2003; 31(13):3429-31. PMC: 169005. DOI: 10.1093/nar/gkg599. View