Sentence examples for datasets and time from inspiring English sources

Reference gene biclustering will only find biclusters relevant for a single reference gene; differential co-expression biclustering requires exactly two well annotated datasets; and time series biclustering requires time series data.

The results of our study not only confirm an association between different variables but also show that the integration of PFP-growth algorithm with Apache Spark framework solve the problems of the large dataset and time consumption due to the capabilities of Apache Spark.

The large spectrum of the data available makes the data integration and curation of new short read datasets harder and time consuming, forcing the need for endless filtering and post-processing data procedures.

Patient movement data are extracted to produce a cohort dataset and time-series analysis of patients transitioning in the following units: the medical ICU (nine beds), surgical ICU (11 bed), coronary care unit (18 beds), step-down unit (nine beds), monitored medical (15 beds), monitored surgical (12 beds), nonmonitored medical (44 beds) and surgical (19 beds).

In analyzing the performance of the ApproxMap algorithm, we considered both the delta size calculated from mapping pairs of RDF datasets and the time spent on this task.

Previous seasonal variability studies have used small datasets and short time intervals.

Note that there is a causal relationship (represented by the arrows) between the number of uniform datasets and the time spent on implementation.

As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set.

In this study, we applied computational approaches to analyze and integrate three ChIP-based datasets and one time-series gene expression data to investigate the dynamic regulatory information for ERα in estrogen-dependent breast cancer MCF7 cells.

A general observation is that for small datasets and clean signals, time, frequency, and time-frequency-based methods report similar accuracies.

The number of iterations in the task of analyzing structural variation is 2 because it runs one time on the original dataset and one time on randomized dataset of the same size.