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Journal article

ABodyBuilder: automated antibody structure prediction with data-driven accuracy estimation

Abstract:

Computational modelling of antibody structures plays a critical role in therapeutic antibody design. Several antibody modelling pipelines exist, but no freely available methods currently model nanobodies, provide estimates of expected model accuracy, or highlight potential issues with the antibody's experimental development. Here, we describe our automated antibody modelling pipeline, ABodyBuilder, designed to overcome these issues. The algorithm itself follows the standard four steps of temp...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1080/19420862.2016.1205773

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Societies, Other & Subsidiary Companies
Department:
Kellogg College
Oxford college:
Kellogg College
Role:
Author
More from this funder
Funding agency for:
Leem, J
Deane, C
Grant:
EP/G037280/1
EP/G037280/1
EP/G037280/1
Roche Diagnostics GmbH More from this funder
Publisher:
Taylor and Francis Publisher's website
Journal:
MAbs Journal website
Volume:
8
Issue:
7
Pages:
1259-1268
Publication date:
2016-01-01
Acceptance date:
2016-06-20
DOI:
EISSN:
1942-0870
ISSN:
1942-0862
Source identifiers:
634057
Language:
English
Keywords:
Pubs id:
pubs:634057
UUID:
uuid:bbf22afe-335c-41a7-a485-32c4cffe3a2c
Local pid:
pubs:634057
Deposit date:
2016-08-11

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