Sentence examples for majority of databases from inspiring English sources

Medical Subject Headings (MeSH) are used to index the majority of databases generated by the National Library of Medicine.

The majority of databases that contain genetic information were collected by medical scientists.

It must be noted that the majority of databases contain images obtained while photographing people specifically, leading to inflated classification quality estimates in comparison with analysis of images obtained in real-life conditions.

However, this is no different really than the set of assumptions that underpin the Standard InChI that is presently utilized in the majority of databases, with one specific caveat.

Following the clear need for use of ontologies in the biomedical domain and the notable work performed by the OBO foundry, it was expected that the majority of databases would be using OBO ontologies.

The majority of databases in the gene-specific subcategory contained only prevalence data but some contained information about gene- disease associations, though these were often limited to the rather older field of single gene disorders.

However, for the broad majority of database entries, there is so far no experimental evidence that the corresponding genes are in fact translated and the resulting proteins persist in the organism.

Abbreviations of protein domains mentioned only once are explained in the text or figure/table legends; for abbreviations of species see Additional file 1. MG performed the majority of database searches and all phylogenetic analyses and wrote parts of the manuscript.

The set of genes that are only found in at most two databases is, compared to the genes found in the majority of the databases, enriched for terms related to protein metabolic processes, like protein phosphorylation, proteolysis, and RNA metabolism (Additional file 2).

The results of this study show that for the majority of pathway databases, the overlap between experimentally obtained target genes and targets reported in transcriptional regulatory pathway databases is surprisingly small and often is not statistically significant.

Since the majority of biological databases are well curated with cross-references, related information can be retrieved ad hoc from dispersed databases using hyperlinks.