Authors
Vadim Demichev, Christoph B Messner, Spyros I Vernardis, Kathryn S Lilley, Markus Ralser
Publication date
2020/1
Journal
Nature methods
Volume
17
Issue
1
Pages
41-44
Publisher
Nature Publishing Group
Description
We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with fast chromatographic methods.
Scholar articles
DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput
V Demichev, CB Messner, SI Vernardis, KS Lilley… - Nature methods, 2020