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Computational prediction methods that predict subcellular localization from the amino acid sequence represent an attractive alternative to experimental methods.
Some methods that predict the sorting signals limit their predictions to N-terminal signal peptides and their cleavage sites (21, 22).
Therefore, methods that predict structural contacts may be valuable for the purpose of structure prediction in membrane proteins, whose available structures are limited.
Objective image-quality research aims to develop methods that predict the subjective quality experience.
Thus, computational methods that predict three-dimensional RNA structures are in high demand.
Currently, only methods that predict content popularity after publication based on the aggregate behavior have been proposed.
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For benchmarking, we use all 96 targets available during CASP7 and compare the results obtained with OnD-CRF to the results of the 15 methods that predicted 93 or more targets.
Molecular docking is a computational method that predicts how a ligand interacts with a receptor.
In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence.
This paper proposes an innovative and flexible simulation method that predicts the dynamic responses of bridges induced by passing vehicles.
A simple bond-order-conservation method that predicts stability of adatom structures on metal surfaces is presented.
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