Sentence examples for many prediction algorithms from inspiring English sources

Both SPs and SAs contain a stretch of hydrophobic residues, and therefore can be incorrectly predicted as TMDs by many prediction algorithms [ 30].

Site accessibility is not considered in many prediction algorithms.

Many prediction algorithms take into account the conservation of the microRNA binding sequence in the mRNA target.

In addition, the performance on the remaining predicted clusters, i.e., those of size four or more is also considered, because many prediction algorithms have been evaluated by known complexes of size four (or three possibly) or more (see, for example, [ 3, 21]).

After the first bioinformatics attempt at predicting plant microRNAs [5], many microRNA prediction algorithms, for both fly (D. melanogaster) and human (H. sapiens), were developed [20], [21], [22].

Indeed, the first step in many structure prediction algorithms is a multiple sequence alignment followed by some sort of covariation measure.

It is also noteworthy that many new prediction algorithms based on the stringent alignment of domain instances can be proposed to predict possible intra- and inter-species PPIs.

These diseases are associated with marked increased risk of subsequent events and death, yet have been excluded from many risk prediction algorithms.

Chronic disease, such as heart failure and peripheral arterial disease, account for a substantial proportion of initial lifetime CVD presentations, yet are been excluded from many risk prediction algorithms.

Past work produced many target prediction algorithms based on miRNA-target sequence paring including TargetScan [ 3- 5], miRanda [ 6, 7], PicTar [ 8], mirTarget [ 9, 10], PITA [ 11], DianamicroT [ 12] and others [ 13- 21].

Many structure prediction algorithms can also compute the probability of base-pairing (which is more analogous to SHAPE reactivity) by summing the rows or columns of the predicted partition function matrix [ 48, 50].