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Publication for TargetBoost
The miR 125 family is an important regulator of the expression and maintenance of maternal effect genes during preimplantational embryo development
[…] ne the regulatory mechanisms between miRNAs and proteins. Numerous computational approaches for miRNA target prediction have already been developed, such as TargetScan, miRanda, miRmap, Diana-MicroT, TargetBoost, miTarget, MirTarget2, TargetSpy, TargetMiner, MultiMiTar, NBmiRTar and microT-ANN . Because each algorithm has its own set of limitations, multiple computational algorithms are commonly […]
Advances in the Techniques for the Prediction of microRNA Targets
[…] achine learning algorithms can also be used to intelligently search for the parameters with most predictive power of genuine miRNA binding sites. An example of a method for miRNA target prediction is TargetBoost, which uses machine learning based on a set of validated miRNA targets in lower organisms to create weighted sequence motifs that capture binding characteristics between miRNAs and their t […]
One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms
[…] ly. Representatives from this line are briefly described as follows. Since machine learning algorithms strongly rely on experimental data, we also specify the size of the respective training dataset.•TargetBoost consists of a boosting algorithm that assigns weights to sequence patterns of 30 nucleotides. The negative dataset used for training consists of 300 randomly-generated sequences, and the […]
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