Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-01

AUTHORS

Ngoc Hieu Tran, Rui Qiao, Lei Xin, Xin Chen, Chuyi Liu, Xianglilan Zhang, Baozhen Shan, Ali Ghodsi, Ming Li

ABSTRACT

We present DeepNovo-DIA, a de novo peptide-sequencing method for data-independent acquisition (DIA) mass spectrometry data. We use neural networks to capture precursor and fragment ions across m/z, retention-time, and intensity dimensions. They are then further integrated with peptide sequence patterns to address the problem of highly multiplexed spectra. DIA coupled with de novo sequencing allowed us to identify novel peptides in human antibodies and antigens. More... »

PAGES

63-66

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41592-018-0260-3

DOI

http://dx.doi.org/10.1038/s41592-018-0260-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110453075

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30573815


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