Sentence examples for dataset processing from inspiring English sources
The design of this platform is composed of four layers: the infrastructure services layer, the virtualization layer, the dataset processing layer, and the services layer.
We thank Junping Jing for providing the mapping results of Affymetrix U133 probe sets onto human RefSeq/genome, and Stephen Tanner for his initial work in implementing the cyber-T algorithm in Python and establishing a general framework for automatic GEO dataset processing.
HW, HY, JA, GH were involved in collecting the samples in the dataset, processing the samples for the SELDI analysis, SELDI MS acquisition, data processing with CiphergenExpress and in verifying the quality of the peaks (section 2.3).
Scientific requirements arose during the process highlighted the needs for easy parameter setting, fully embarrassingly parallel computations and large-scale input dataset processing.
Apparently, a relatively small number of such studies are related to the complexity of extensive dataset processing, as well as the issues concerning an automated interpretation of HF radar data.
Analysis involves extracting the data of interest from all the available raw data in a dataset and processing it into a data product.
Also the use of ICA to separate cranial muscle activity (>30 Hz) and motion artifact result in a more valid EEG dataset for processing.
Because cell type greatly influences expression patterns [ 28], and because our microarray datasets consisted of cell-type-specific batches that confound effects from these two variables, each cell type was treated as a separate dataset for processing.
Here the importance of a predictor to the RFML model was assessed by randomly permuting the values of the factor within a validation dataset, and processing the validation data through the regression trees.
For detailed information on the visual capabilities of NetWalker, along with other functionalities for dataset import, processing, heatmap clustering, GeneConnector and inter-operability with external applications, including R, please see Manual in the Additional file 1. Table 1 contains a summary of comparison of functionalities in NetWalker with other popular software applications.
In this article, we have demonstrated a methodology which, by modelling the analysis and decision process of an experienced scientist, can substantially speed up validation of a large scale phosphoproteomics dataset by processing the data with 80 95% confidence in the positive validations and with a high sensitivity.
