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Accuracy of protein hydropathy predictions.

Jääskeläinen, Satu; Riikonen, Pentti; Salakoski, Tapio and Vihinen, Mauno LU (2010) In International Journal of Data Mining and Bioinformatics 4(6). p.735-754
Abstract
Hydropathy is a dominant force in protein folding. Sequence-based hydropathy predictions are widely used, without knowledge about their accuracy and reliability. We investigated the prediction accuracy of 56 hydropathy scales by correlating predicted values with the accessible surface area in known protein structures. Results for different amino acids vary greatly within each scale. We also investigated prediction accuracies of amino acids separately in secondary structural elements and in protein fold families. Despite very low overall correlation, hydropathy predictions can still be used if the shape of the plot is important instead of the prediction values.
Please use this url to cite or link to this publication:
author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Computational Biology: methods, Proteins: chemistry, Proteins: metabolism
in
International Journal of Data Mining and Bioinformatics
volume
4
issue
6
pages
735 - 754
publisher
Inderscience
external identifiers
  • pmid:21355504
  • scopus:78650482076
ISSN
1748-5673
language
English
LU publication?
no
id
c462f08b-f26a-4692-a513-89eb7f0bc5eb (old id 3634747)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/21355504?dopt=Abstract
date added to LUP
2013-06-12 20:38:23
date last changed
2018-05-29 10:51:54
@article{c462f08b-f26a-4692-a513-89eb7f0bc5eb,
  abstract     = {Hydropathy is a dominant force in protein folding. Sequence-based hydropathy predictions are widely used, without knowledge about their accuracy and reliability. We investigated the prediction accuracy of 56 hydropathy scales by correlating predicted values with the accessible surface area in known protein structures. Results for different amino acids vary greatly within each scale. We also investigated prediction accuracies of amino acids separately in secondary structural elements and in protein fold families. Despite very low overall correlation, hydropathy predictions can still be used if the shape of the plot is important instead of the prediction values.},
  author       = {Jääskeläinen, Satu and Riikonen, Pentti and Salakoski, Tapio and Vihinen, Mauno},
  issn         = {1748-5673},
  keyword      = {Computational Biology: methods,Proteins: chemistry,Proteins: metabolism},
  language     = {eng},
  number       = {6},
  pages        = {735--754},
  publisher    = {Inderscience},
  series       = {International Journal of Data Mining and Bioinformatics},
  title        = {Accuracy of protein hydropathy predictions.},
  volume       = {4},
  year         = {2010},
}