Sentence examples for datasets integration from inspiring English sources

A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists.

Moreover, desirable advanced features such as resilience to hardware problems, the ability to re-use intermediate datasets, integration with HPC cluster resources, etc. must all be written from scratch.

We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration).

The steps cover (i) legacy data identification and collection, (ii) data selection, (iii) database development and population, (iv) data harmonization and display, and (v) dataset integration.

We also highlight the importance of standardization and the challenges associated with dataset integration in the drive to build a systematic framework for effective harnessing of plant metabolic diversity.

The source dataset integration augments the network mainly in PPIs.

For brevity, we refer to our approach as MDI, simply as a shorthand for 'Multiple Dataset Integration'.

Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed.

In general, however, when coupled with one of several cross-experiment dataset integration tools, aRrayLasso will enable mining of the remarkable and untapped historical pool of microarray datasets for large-scale metastudies for well-powered discovery.

Accordingly, we propose a methodology for a holistic comparative analysis and ranking of cancer diagnostic tests through dataset integration and imputation of missing values, using urothelial carcinoma (UC) as a case study.

There have been several previous attempts at dataset integration, some of which have tried to apply regression based models [ 2], while some have validated the ChIP-Seq identified targets by transcriptionally silencing the TF and observing the effect on gene expression [ 3, 4].