2023
DOI: 10.1016/j.compbiomed.2022.106440
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A systematic review on the state-of-the-art strategies for protein representation

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Cited by 4 publications
(2 citation statements)
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“…Computing numerical descriptors for protein targets is a complex task with various existing methodologies [33]. Descriptors based on protein 3D structure have become an attractive approach due to the ever-increasing data on 3D protein structure, complemented by the accurate predictions of AlphaFold [16].…”
Section: Descriptors For Target Proteinsmentioning
confidence: 99%
“…Computing numerical descriptors for protein targets is a complex task with various existing methodologies [33]. Descriptors based on protein 3D structure have become an attractive approach due to the ever-increasing data on 3D protein structure, complemented by the accurate predictions of AlphaFold [16].…”
Section: Descriptors For Target Proteinsmentioning
confidence: 99%
“…A key step for machine learning is peptide representation [9,10], whereby relevant structural information is converted into numerical formats for model training. Several strategies can be adopted to encode peptide information, e.g., via description of physicochemical features [10], one-hot encoding [11], and/or evolutionary information [12].…”
Section: Introductionmentioning
confidence: 99%