Proteins of well-defined structures can be designed without backbone readjustment by a statistical model.

No abstract is available for this paper.

• Publication year

  2016

• Venue

  Journal of Structural Biology

• Publication date

  2016-12-01

• Fields of study

  Biology, Medicine, Chemistry

• Identifiers
  DOI 10.1016/j.jsb.2016.08.002PMID 27522946
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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  1996influential reference
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