Sentence examples for and availability of datasets from inspiring English sources

The value of these things is the result of the ingenuity, competence and (perhaps above all) hard work of human beings, not something that follows automatically from the mere presence and availability of datasets over the web in a form which permits their reuse.

The limitation of the study was the laboratory validation of the targets and availability of datasets in the TCGA.

In parallel, the structure of collaboration has attracted much attention, and collaboration networks have become a central example for the study of complex networks, thanks to the high quality and availability of the datasets [9].

A high level of microbial diversity and availability of metagenomic datasets obtained using various sequencing techniques make the human gut microbiome a promising object for studying CRISPR systems.

The generation and availability of consistent datasets from human and rodents representing a variety of perturbations carried out on the same tissue or cell types under identical conditions would be highly valuable to further our understanding and use of mouse and rat models as predictors for applications in biomedical research.

Fortunately, with the significant number of studies based on gene expression profiling in the last decade and the availability of datasets for reanalyses and meta-analyses, the field of gene expression profiling has matured.

Details of the numbers and anatomical subsites of procured tumor samples, microarray platforms used, analytical methods conducted, original identifiers reported, information regarding fold changes, and the availability of datasets were provided in Table S1.

Contingent upon generation and availability of high quality datasets, whole genome tiling array transcriptomes and deep smRNA datasets such as for rice [85], [86] and other species will be suitable subjects for further computational methods testing and analysis.

As the quality and availability of these environmental datasets continues to increase, so do opportunities for integration and meaningful comparisons between them to be made.

Biomarker discovery using this methodology is necessarily limited by quantity, quality, and availability of public microarray datasets for a disease.

Spatio-temporal data analysis has recently gained considerable attention from both the research and practitioner communities because of the increasing availability of datasets with prominent spatial and temporal data elements.