Sentence examples for based classifier to predict from inspiring English sources

Using the 29 miRNA-host gene pairs of Baskerville et al., we have constructed a SVM based classifier to predict whether an intronic miRNA is high co-expressed with its host gene.

Using this set of proteins and proteins deemed not to be urine excretory, we have identified a list of distinguishing features between these two classes of proteins and trained a support vector machine (SVM) based classifier to predict if a given protein might be excreted into urine.

We developed SVM-based classifier to predict domain swapping event using sequence and structure-derived features.

We have developed a SVM-based classifier to predict domain swapping events using a set of features derived from sequence and structural data.

As pre-filter parameters would be very useful in filtering the pseudo pre-miRNAs from huge number of similar pre-miRNA sequences, those pre-filters were incorporated into the SVM-based classifier to predict novel pre-miRNAs.

For this reason, we use weighted sparse representation based classifier to build a computational classification system for predicting protein interaction.

Based on these results, we found the 11-gene based Naïve Bayes or logistic regression based classifiers to perform better compared to the 183-gene classifiers for predicting class membership.

Here, we developed a pathway based classifier approach to predict presence or absence of CIS in patients suffering from non muscle invasive bladder cancer.

We developed a pathway based classifier approach to predict presence or absence of CIS in patients suffering from non muscle invasive bladder cancer.

Here, we used a pathway based classifier approach to predict a clinical parameter in patients suffering from non muscle invasive bladder cancer.

We next explore a model based on a Bayesian classifier to predict whether a given response comes from a legitimate user (i.e., u) or an adversary (i.e., u ′) based on k response features (f 1…f k ).