Year: 2015
Type: conference-paper
Abstract: Targeted proteomics techniques such as Selected Reaction Monitoring (SRM) have become very popular for protein quantification due to their high sensitivity and reproducibility. However, these rely on the selection of optimal transitions, which are not always known in advance and may require expensive and time-consuming discovery experiments to identify. We propose a computer program for the automated identification of optimal transitions using machine learning and show encouraging results when compared to a widely used spectral library.
Source: Lirias
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2525587445