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Protein asparagine deamidation prediction based on structures with machine learning methods

Protein asparagine deamidation prediction based on structures with machine learning methods

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1922176765

Protein asparagine deamidation prediction based on structures with machine learning methods

About this item

Full title

Protein asparagine deamidation prediction based on structures with machine learning methods

Author / Creator

Publisher

United States: Public Library of Science

Journal title

PloS one, 2017-07, Vol.12 (7), p.e0181347-e0181347

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isomerization, glycosylation, oxidation etc. A more accurate prediction method for potential hotspot res...

Alternative Titles

Full title

Protein asparagine deamidation prediction based on structures with machine learning methods

Authors, Artists and Contributors

Author / Creator

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_1922176765

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1922176765

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0181347

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