DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

Abstract:

: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.

journal_name

Nat Methods

journal_title

Nature methods

authors

Demichev V,Messner CB,Vernardis SI,Lilley KS,Ralser M

doi

10.1038/s41592-019-0638-x

subject

Has Abstract

pub_date

2020-01-01 00:00:00

pages

41-44

issue

1

eissn

1548-7091

issn

1548-7105

pii

10.1038/s41592-019-0638-x

journal_volume

17

pub_type

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