Mar 14, 2017 · Conclusion. In this paper, we present a novel method FIRE for boosting the performance of protein-RNA interaction prediction by selecting high- ...
Mar 14, 2017 · Selecting high-quality negative samples for effectively predicting protein-RNA interactions. BMC Syst Biol. 2017 Mar 14;11(Suppl 2):9. doi ...
Mar 14, 2017 · Concretely, we generate negative samples like this: give a threshold value st (st is set to 0, 0.2, 0.4, 0.7 and 1.0 respectively), we select ...
The identification of Protein-RNA Interactions (PRIs) is important to understanding cell activities. Recently, several machine learning-based methods have ...
A novel method to generate reliable negative samples is proposed for boosting the performance of PRI prediction and all classifiers achieve substantial ...
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Selecting high-quality negative samples for effectively predicting protein-RNA interactions. Overview of attention for article published in BMC Systems ...
Dec 15, 2022 · In this opinion paper we revisit the problem of choosing negative examples for the task of predicting protein-protein interactions.
Selecting high-quality negative samples for effectively predicting protein-RNA interactions. Overview of attention for article published in BMC Systems ...
Selecting high-quality negative samples for effectively predicting protein-RNA interactions. 蛋白質-RNA相互作用を効果的に予測するための高 ...
We propose a novel deep reinforcement learning-based model to screen reliable negative samples from unlabeled samples, named SURE.