Protein secondary structure prediction

Geoffrey J. Barton (Lead / Corresponding author)

Research output: Contribution to journalArticle

72 Citations (Scopus)

Abstract

The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.

Original languageEnglish
Pages (from-to)372-376
Number of pages5
JournalCurrent Opinion in Structural Biology
Volume5
Issue number3
DOIs
Publication statusPublished - Jun 1995

Fingerprint

Secondary Protein Structure
Discriminant Analysis
X-Rays
Proteins
Machine Learning

Keywords

  • Animals
  • Humans
  • Predictive value of tests
  • Protein structure, Secondary
  • Proteins
  • Sequence alignment
  • Sequence analysis

Cite this

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title = "Protein secondary structure prediction",
abstract = "The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.",
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Protein secondary structure prediction. / Barton, Geoffrey J. (Lead / Corresponding author).

In: Current Opinion in Structural Biology, Vol. 5, No. 3, 06.1995, p. 372-376.

Research output: Contribution to journalArticle

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AU - Barton, Geoffrey J.

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AB - The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.

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KW - Predictive value of tests

KW - Protein structure, Secondary

KW - Proteins

KW - Sequence alignment

KW - Sequence analysis

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