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 in two cases of 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 in two cases likewise of 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 07:10, 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 in two cases likewise of 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
...
