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• W2952090638 abstract "The long awaited challenge of post-genomic era and systems biology research is computational prediction of protein-protein interactions (PPIs) that ultimately lead to protein functions prediction. The important research questions is how protein complexes with known sequence and structure be used to identify and classify protein binding sites, and how to infer knowledge from these classification such as predicting PPIs of proteins with unknown sequence and structure. Several machine learning techniques have been applied for the prediction of PPIs, but the accuracy of their prediction wholly depends on the number of features being used for training. In this paper, we have performed a survey of protein features used for the prediction of PPIs. The open research challenges and opportunities in the area have also been discussed." @default.
• W2952090638 created "2019-06-27" @default.
• W2952090638 creator A5080855773 @default.
• W2952090638 date "2017-01-01" @default.
• W2952090638 modified "2023-09-24" @default.
• W2952090638 title "Protein Features Identification for Machine Learning-Based Prediction of Protein-Protein Interactions" @default.
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• W2952090638 doi "https://doi.org/10.1007/978-981-10-6544-6_28" @default.
• W2952090638 hasPublicationYear "2017" @default.
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