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... machine learning approaches. Nucleic Acids Research, 2019. 47(20): e127. [51] Chen Z, et al. iLearn: An integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence ...
... DNA methylation data. Epigenomics 11(13):1469–1486. https://doi.org/10.2217/epi-2019-0206 Cai L, Wu Y, Gao J (2019) ... iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling ...
... model proposed in this paper can be used to predict the anticancer peptide conveniently, quickly and accurately. DATA AVAILABILITY STATEMENT The raw data supporting the conclusions of this article will be In this paper, the feature ...
... features from their sequence and structure . bioRxiv p . 599126 ( 2019 ) updates Inferences on Mycobacterium Leprae Host Immune Response Escape and ProPythia : Python for Protein Classification Using Machine Learning 41 References.
... model 0.9533 0.8995 0.9539 0.8445 0.8802 0.9088 0.8663 7 Conclusion We presented a machine learning-based prediction model for DTIs. We use random under-sampling to deal with the imbalance of the datasets. To encode features such as CDK ...
... features extraction and selection from protein and peptide sequences. Bioinformatics 34, 2499–2502. doi: 10. 1093/bioinformatics/bty140 Chen, Z., Zhao, P., Li, F., Marquez-Lago, T. T., Leier, A., Revote, J., et al. (2020). iLearn: an ...
... sequence features to improve CRISPR sgRNA efficacy. IEEE Access 5, 26582–26590. doi: 10.1109/ACCESS.2017.2775703 Chen, L., Zhang, S., Pan, X., Hu, X., Zhang, Y. H., Yuan, F., et al. (2019b). HIV infection alters the human epigenetic ...
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... analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. BH, HC, and JH REFERENCES Banks, W. A. (2016). From Blood-Brain Barrier to Blood-Brain Interface: New ...