… -redundant dataset of sequence segments for which we have high-resolution data about
protein–protein interactions (true positives) and those that are not known to interact externally (…

… is better than that of other sequence-based PPI prediction methods … sequence information,
this method could be applied to the exploration of networks for any newly discovered protein …

… We compare the performance of only using protein amino acid sequence information or
position information to make predictions. The auPR is the mean of 10-fold cross validation …

… protein sequences, we propose a novel method to fully describe key information of protein-protein
interaction. … , which is commonly used for protein sequence classification [26, 27]. Here …

… performance in predicting mRNA-protein interactions. Further, our results suggest that
sequences of mRNAs and proteins carry sufficient information to allow reasonable predictions …

… The results of the wet experiment provided evidence for the effectiveness of our method
of de novo prediction of protein–RNA interaction only by sequence information. …

… 83% when using sequences and predicted protein and RNA … validated ncRNA-protein
interaction pairs from different … construction of ncRNA-protein interaction networks. The RPI-…

… sequence profile alignments and protein–protein interaction networks. Large-scale benchmark
tests show that the new hybrid COFACTOR approach significantly improves the function …

… Abstract: With a huge amount of protein sequence data, the computational method for
protein–protein interaction (PPI) prediction using only the protein sequences information have …

… and predict PPIs from sequence information alone. Our … data and evolutionary information of
a protein pair under prediction. … to predict homodimeric interactions where other methods fail …