Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 14626018

Database research.

Margaret Ross Kraft
View original source ↗Export metadata ↓

Abstract

According to Dochterman and Grace (2001), forward movement as a scientific discipline requires generation of data about patients and health care delivery systems. The science of nursing may be defined by how nursing data is collected and used. Nursing data must be captured and analyzed to validate the impact of nursing care, to ensure adequate financial support for nursing, to allow research of nursing practice, and to be sure nursing has a voice in the development of health care policy. Research that transforms data into meaningful information can be useful for health care providers, policy makers, and the public served by nursing.

Explore related subjects

Data CollectionData Interpretation, StatisticalDatabases, FactualHumansNursing ResearchResearch DesignJournal ArticleReview

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Margaret Ross Kraft. 2003. Database research.. https://pubmed.ncbi.nlm.nih.gov/14626018/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2004

A model for random sampling and estimation of relative protein abundance in shotgun proteomics.

Proteomic analysis of complex protein mixtures using proteolytic digestion and liquid chromatography in combination with tandem mass spectrometry is a standard approach in biological studies. Data-dependent acquisition is used to automatically acquire tandem mass spectra of peptides eluting into the mass spectrometer. In more complicated mixtures, for example, whole cell lysates, data-dependent acquisition incompletely samples among the peptide ions present rather than acquiring tandem mass spectra for all ions available. We analyzed the sampling process and developed a statistical model to accurately predict the level of sampling expected for mixtures of a specific complexity. The model also predicts how many analyses are required for saturated sampling of a complex protein mixture. For a yeast-soluble cell lysate 10 analyses are required to reach a 95% saturation level on protein identifications based on our model. The statistical model also suggests a relationship between the level of sampling observed for a protein and the relative abundance of the protein in the mixture. We demonstrate a linear dynamic range over 2 orders of magnitude by using the number of spectra (spectral sampling) acquired for each protein.

Data Collection↗