Sentence examples similar to a data analysis where from inspiring English sources

Tanaka et al. proposed an interesting data analysis where human behavioral data of a Markov decision task were analyzed according to the temporal difference (TD) learning rule and applied for BOLD data analysis in human subjects [33].

It is a crucial preprocessing technique for effective data analysis, where only a subset from the original data features is chosen to eliminate noisy, irrelevant or redundant features.

Genome-scale metabolic model reconstructions can also be used as a scaffold for integrated data analysis, where the network structure of the model is the basis for the integration of omics data in order to gain more mechanistic knowledge of the cell's behavior in different environments or under different conditions.

The study introduces and elaborates on a certain perspective of biomedical data analysis where data structure is revealed through fuzzy clustering.

Data clustering is a common technique for statistical data analysis where data is partitioned into smaller sub-groups with their members sharing a common property [5].

The authors proposed a map-reduce implementations for proteomics data analysis where 2D peaks are picked at map level and further analyzed at reduce level [63].

Survival analysis is a collection of statistical procedures for data analysis where the outcome variable of interest is time until an event occurs.

Therefore, we used a combined cross-sectional and longitudinal approach for the data analysis, where patients diagnosed during 2004 2007 had an associated resource use for 2006 2008.

This is especially important in gene expression data analysis where time points are a scarce and valuable resource.

Often, GLMs are used for exploratory data analysis, where one starts with a complex full model including interaction terms and then simplifies by removing non-significant terms.

This strict correction is less appropriate for genomic data analysis, where the cost of a false positive is relatively low, the number of observations is relatively low, and the number of tests is high.