Difference between revisions of "Sequence-based predictions (Phenylketonuria)"
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== Summary == |
== Summary == |
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| − | Sequence-based prediction approaches are useful to predict a variety of structural and functional properties of proteins. Here we used different methods to provide useful information about our protein sequence and some other given proteins (in brackets): |
+ | Sequence-based prediction approaches are useful to predict a variety of structural and functional properties of proteins. Here, we used different methods to provide useful information about our protein sequence and some other given proteins (in brackets): |
* ReProf for secondary structure prediction (P10775, Q9X0E6, Q08209) |
* ReProf for secondary structure prediction (P10775, Q9X0E6, Q08209) |
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* IUPred and MD (MetaDisorder) for the prediction of the disorder |
* IUPred and MD (MetaDisorder) for the prediction of the disorder |
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Revision as of 07:06, 11 May 2013
Contents
Summary
Sequence-based prediction approaches are useful to predict a variety of structural and functional properties of proteins. Here, we used different methods to provide useful information about our protein sequence and some other given proteins (in brackets):
- ReProf for secondary structure prediction (P10775, Q9X0E6, Q08209)
- IUPred and MD (MetaDisorder) for the prediction of the disorder
- PolyPhobius and MEMSAT-SVM to predict transmembrane helices (P35462, Q9YDF8, P47863)
- SignalP to predict signal peptides
- GOPET and ProtFun2.0 to predict GO terms
- Pfam with a sequence search to find out more about the Pfam family of our protein
Secondary structure
...
Disorder
...
IUPred
...
MD (MetaDisorder)
...
Transmembrane helices
...
PolyPhobius
...
MEMSAT-SVM
...
Signal peptides
...
GO terms
...
Pfam
...
