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

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 i...

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Detalles Bibliográficos
Autores principales: Demichev, Vadim, Messner, Christoph B., Vernardis, Spyros I., Lilley, Kathryn S., Ralser, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949130/
https://www.ncbi.nlm.nih.gov/pubmed/31768060
http://dx.doi.org/10.1038/s41592-019-0638-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949130/
https://www.ncbi.nlm.nih.gov/pubmed/31768060
http://dx.doi.org/10.1038/s41592-019-0638-x

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