SpliceSCANNER: An Accurate and Interpretable Deep Learning-Based Method for Splice Site Prediction
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-4749-2_38
Reference20 articles.
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2. Burset, M., Seledtsov, I.A., Solovyev, V.V.: SpliceDB: database of canonical and non-canonical mammalian splice sites. Nucl. Acids Res. 29, 255–259 (2001)
3. Pertea, M., Lin, X., Salzberg, S.L.: GeneSplicer: a new computational method for splice site prediction. Nucl. Acids Res. 29, 1185–1190 (2001)
4. Trapnell, C., Pachter, L., Salzberg, S.L.: TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009)
5. Kim, D., Langmead, B., Salzberg, S.L.: HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015)
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1. SpliceCannon: A novel framework for the prediction of canonical and non-canonical splice sites based on deep learning;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05
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