Different miRNA-target prediction algorithms predict targets with different techniques and criteria including base pairing, target accessibility and evolutionary conservation of target site.
Although, many plant miRNA target prediction tools may be optimized to predict targets with high specificity in Arabidopsis, such optimized thresholds may not be suitable for many targets in non-Arabidopsis species.
As a consequence several computational prediction methods have been devised in order to predict targets for follow up experimental validation.
Such approaches are designed to predict targets for orphan compounds early in the drug development phase, with the predictions forming the base of an experimental confirmation afterwards.
Use of in silico tools to predict targets of small molecules has drawn more and more attentions in recent years.
They are used in various approaches to predict targets for genetic interventions in order to increase production of a molecule of interest via a host cell.
