Plant Protein Classification Using K-mer Encoding
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48984-6_8
Reference13 articles.
1. Öncül, A.B., Çelik, Y.: A hybrid deep learning model for classification of plant transcription factor proteins. SIViP 17, 2055–2061 (2023)
2. Nedyalkova, M., Vasighi, M., Azmoon, A., Naneva, L., Simeonov, V.: Sequence-based prediction of plant allergenic proteins: machine learning classification approach. ACS Omega 8(4), 3698–3704 (2023). https://doi.org/10.1021/acsomega.2c02842
3. Upadhyaya, S.R., et al.: Evaluating Plant Gene Models Using Machine Learning. Plants 11(12), 1619 (2022). https://doi.org/10.3390/plants11121619
4. Yadav, A.K., Singla, D.: VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques. J. Biosci. 45, 1–9 (2020)
5. Simon, O.A., et al.: K-mer-based machine learning method to classify LTR-retrotransposons in plant genomes. PeerJ 9, e11456 (2021)
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