A Text Mining and Machine Learning Protocol for Extracting Posttranslational Modifications of Proteins from PubMed: A Special Focus on Glycosylation, Acetylation, Methylation, Hydroxylation, and Ubiquitination
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Publisher
Springer US
Link
https://link.springer.com/content/pdf/10.1007/978-1-0716-2305-3_10
Reference47 articles.
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3. Minguez P, Parca L, Diella F et al (2012) Deciphering a global network of functionally associated post-translational modifications. Mol Syst Biol 8:599. https://doi.org/10.1038/msb.2012.31. Available from: https://pubmed.ncbi.nlm.nih.gov/22806145/
4. Khoury GA, Baliban RC, Floudas CA (2011) Proteome-wide post-translational modification statistics: frequency analysis and curation of the swiss-prot database. Sci Rep 1:90. Available from: https://www.nature.com/articles/srep00090?message-global=remove&page=2
5. Wang YC, Peterson S, Loring J (2014) Protein post-translational modifications and regulation of pluripotency in human stem cells. Cell Res 24:143–160. https://doi.org/10.1038/cr.2013.151. Available from: https://www.nature.com/articles/cr2013151
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