RFPR-IDP is a new method which trained with data containing ordered proteins. The predictor is constructed based on the combination of Convolution Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM), in which CNN can capture the local information or motifs of proteins and BiLSTM can learn the long-term dependence information in both directions of proteins. Experimental results show that RFPR-IDP can effectively reduce the false positive rates and accurately predict IDPs from ordered proteins for real world applications.
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Liu Y, Wang X, Liu B.
RFPR-IDP: reduce the false positive rates for intrinsically disordered protein and region prediction by incorporating both fully ordered proteins and disordered proteins.
Brief Bioinform. 2021 Mar 22;22(2):2000-2011. doi: 10.1093/bib/bbaa018. PMID: 32112084; PMCID: PMC7986600.