Sentence examples for be improved by computational from inspiring English sources

Then we present an example of how the current approach to visualize time series of meteorological images can be improved by computational methods, particularly by feature tracking.

Using a recent high-resolution screen of genetic interactions in yeast as a case study, we investigated whether the extraction of pertinent information encoded in the quantitative phenotypic measurements could be improved by computational means.

What remains unclear is the extent to which the quantitative genetic interaction datasets can distinguish the broad spectrum of interaction classes, as compared to existing information on mutation pairs associated with both positive and negative interactions, and whether the scoring of varying degrees of such epistatic effects could be improved by computational means.

These approaches can be improved by computational analyses.

Performance of the tree classification models could have been improved by computational approaches – such as collapsing the data into two classes (supersusceptible and "other"), replicating data to yield groups of equivalent numbers and combining data into a single training set.

The significant overlap between our computational predictions and RNAi screening results suggests that RNAi screen results can be improved by using computational predictions to guide experiments, performing RNAi screens in size-reduced, prioritized subspaces predicted by our model, thus allowing more tissue types or experimental conditions to be tested with the same resources.

Many areas in health care such as diagnosis, prognosis, and screening can be improved by utilizing computational intelligence [ 28].

Calculation of unbiased accuracy of within breed [ 8] and across breed [ 12] estimated breeding values can be improved by reducing the computational time required of calculation or reducing the sampling error for a given computational time.

The methods require either sequence or structural information and present different limitations, their performance depending on the impact on structural stability or intermolecular interactions of the mutation; methods are often complementary in approach to others (43) implying that overall prediction quality could be improved by combining different computational methods.

We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

For example, Aghaeepour et al.21 showed that the accuracy of cell population identifications from flow cytometry data can be improved by combining predictions from individual computational algorithms.