Results 241 to 250 of about 415,112 (277)

Predicting secondary structures of proteins

IEEE Engineering in Medicine and Biology Magazine, 2005
The article presents the application of a new machine-learning algorithm for the prediction of secondary structures of proteins. The logical analysis of data (LAD) algorithm was applied to recognize which amino acids properties could be analyzed to deliver additional information, independent from protein homology, useful in determining the secondary ...
J. Blazewicz, P.L. Hammer, P. Lukasiak
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Improving Protein Secondary-Structure Prediction by Predicting Ends of Secondary-Structure Segments

2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005
Motivated by known preferences for certain amino acids in positions around a-helices, we developed neural network-based predictors of both N and C a-helix ends, which achieved about 88% accuracy. We applied a similar approach for predicting the ends of three types of secondary structure segments.
U. Midic, A.K. Dunker, Z. Obradovic
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Protein Secondary Structure Prediction Approaches

2020
The prediction of protein secondary structure from a protein sequence provides useful information for predicting the three-dimensional structure and function of the protein. In recent decades, protein secondary structure prediction systems have been improved benefiting from the advances in computational techniques as well as the growth and increased ...
Fawaz H. H. Mahyoub, Rosni Abdullah
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Protein secondary structure prediction using local alignments

Journal of Molecular Biology, 1997
The accuracy of secondary structure prediction methods has been improved significantly by the use of aligned protein sequences. The PHD method and the NNSSP method reach 71 to 72% of sustained overall three-state accuracy when multiple sequence alignments are with neural networks and nearest-neighbor algorithms, respectively.
A A, Salamov, V V, Solovyev
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Protein secondary structure prediction with dihedral angles

Proteins: Structure, Function, and Bioinformatics, 2005
AbstractWe present DESTRUCT, a new method of protein secondary structure prediction, which achieves a three‐state accuracy (Q3) of 79.4% in a cross‐validated trial on a nonredundant set of 513 proteins. An iterative set of cascade–correlation neural networks is used to predict both secondary structure and ψ dihedral angles, with predicted values ...
Matthew J, Wood, Jonathan D, Hirst
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Evaluation of secondary structure predictions in proteins

Biochimica et Biophysica Acta (BBA) - Protein Structure, 1977
Data of 33 proteins are used to compare four methods which predict secondary structure from the amino acid sequence. The prediction of alpha-helices according to the histogram method of Argos et al. (Argos, P., Schwarz, J. and Schwarz, J. (1976) Biochim. Biophys.
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Prediction of super-secondary structure in proteins

Nature, 1983
Various methods for the prediction of secondary structure from amino acid sequence can consistently achieve on average 60% accuracy when tested for several proteins. Improvement on this value has proved difficult, despite increasing the size of the data set and refining predictive techniques.
W R, Taylor, J M, Thornton
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Secondary structure prediction and protein design.

Biochemical Society symposium, 1990
For non-homologous proteins, and after cross-validation, the methods reviewed in this article exhibit a probability index (percentage of correctly predicted residues per predicted residues) of 59-65.5% according to the methods employed with a standard deviation of 7% for three conformational states: alpha-helix, beta-strand and coil.
Garnier, Jean, Levin, Jonathan, Gibrat, Jean-François, Biou, Valérie   +3 more
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Accurate Prediction of Protein Secondary Structural Content

Journal of Protein Chemistry, 2001
An improved multiple linear regression (MLR) method is proposed to predict a protein's secondary structural content based on its primary sequence. The amino acid composition, the autocorrelation function, and the interaction function of side-chain mass derived from the primary sequence are taken into account.
Z, Lin, X M, Pan
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Evaluating Predictions of Secondary Structure in Proteins

Biochemical and Biophysical Research Communications, 1994
To learn how secondary structure assignments diverge during divergent evolution, pairs of proteins with solved crystal structures were aligned and their assignments compared as a function of evolutionary distance. Residues assigned in one structure to a helix or a strand are frequently paired with residues assigned in the other to a coil.
T F, Jenny, S A, Benner
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