Sentence examples for predictions to study from inspiring English sources

Fourthly, we performed both miRNA-mRNA and miRNA-protein correlation analyses and integrated these with computational target predictions to study potential direct targets of miRNAs.

In this paper we use computational RNA secondary structure prediction to study structural requirements for efficient splicing in yeast.

The most crucial aspect of the experimental design is the combination of data from multiple expression profiling methods, genomic sequence and in silico prediction to study miRNA function.

The Mirror Station (MS) was designed to validate modeling predictions and to study the suppression of deposition inside of diagnostic ducts.

None of the resistance databases mentioned above provide an automated prediction tool to study structural changes leading to drug resistance caused by mutations in human kinases.

Such novel architecture provides the opportunity to conduct more in-depth analysis of personality trait prediction and to study the relationships between the three concepts mentioned before (facial muscle activity, emotion, and personality trait).

The ability of these models to be applied on coating development was demonstrated applying the prediction criteria to study the effect of coating thickness and the coating intrinsic specific wear rate.

A field experiment using a split-plot randomized complete block design with three replications was carried out to determine relationships between spectral indices and wheat grain yield (GY), to compare the performance of four vegetation indices (VIs) for GY prediction, and to study the feasibility of VI to estimate grain protein content (GPC) in winter wheat.

We used our Ta prediction data to study associations between Ta and live birth outcomes among singleton births in Massachusetts during 2000 2008, including term birth weight, LBW (< 2,500 g) among term births, preterm birth (< 37 weeks), and gestational age.

In the presented study, we make use of these new PM2.5 prediction data to study the association between long (exposure during the whole birth period and last trimester) and short term PM2.5 exposure (exposure during the last month of pregnancy) and birth weight and premature birth in eastern Massachusetts between the years 2000 2008.

As opposed to prior work, in this work, our goal is to investigate ensemble-based semi-supervised learning as a potential solution for splice site prediction and to study the effects of imbalanced distributions on semi-supervised algorithms when labeled data is sparse.