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It is always a difficult call to predict the development of a team four years hence.

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c, number of true SFP calls and percentage of true calls to predicted SFP probes by sequence analysis.

In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations.

This work presents a review of the findings into the ability of a digitally based particle packing algorithm, called DigiPac, to predict bed structure in a variety of packed columns, for a range of generic pellet shapes frequently used in the chemical and process engineering industries.

We developed a composite machine-learning based algorithm, called ANGLOR, to predict real-value protein backbone torsion angles from amino acid sequences.

In this paper, we introduce a novel genetic algorithm called GRNAs to predict the RNA-RNA interaction.

Wu et al. [ 5] develop a tool called CIPHER to predict disease genes based on a global concordance between a PPI network and a phenotype network.

Based on this consideration, we have designed a support vector machine (SVM -based claSVM -basedalled GolgiP, to prediclassifierlgi-localledd transmembrane proteins and non-transmembrane proteins.

We further develop a statistical approach called DCPred to predict possible drug combinations and validate this approach based on a benchmark dataset with all the known effective drug combinations.

To gain additional insights into prediction, DREME [ 26] was performed on the called peak sequences to predict the motif of the mA methylation site.

But it has since developed an algorithm, which it calls reference rank, to predict whether a video will go viral when it has had as few as 10,000 views.

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