John‐Marc Chandonia, University of California, San Francisco, California, USA
Published online: April 2001
DOI: 10.1038/npg.els.0003039
Secondary structure prediction methods are computational algorithms that predict the secondary structure of a protein (i.e. helices, strands and turns) from the primary structure (the amino acid sequence).
Keywords: neural networks; nearest neighbour; secondary structure prediction
| References | |
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| Further Reading | |
| Barton GJ (1995) Protein secondary structure prediction. Current Opinion in Structural Biology 5: 372–376. | |
| Bohm G (1996) New approaches in molecular structure prediction. Biophysical Chemistry 59: 1–32. | |
| Bowie JU, Luthy R and Eisenberg D (1991) A method to identify protein sequences that fold into a known three-dimensional structure. Science 253: 164–170. | |
| Fischer D and Eisenberg D (1996) Protein fold recognition using sequence-derived predictions. Protein Science 5: 947–955. | |
| Kabsch W and Sander C (1983) How good are predictions of protein secondary structure? FEBS Letters 155: 179–182. | |
| Rost B and O'Donoghue S (1997) Sisyphus and prediction of protein structure. Computer Applications in the Biosciences 13: 345–356. | |
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