TY  - JOUR
AU  - Zimmermann, O.
AU  - Hansmann, U. H. E.
TI  - Support Vector Machines for Prediction of Dihedral Angle Regions
JO  - Bioinformatics
VL  - 22
SN  - 1367-4803
CY  - Oxford
PB  - Oxford University Press
M1  - PreJuSER-54190
SP  - 3009
PY  - 2006
N1  - Record converted from VDB: 12.11.2012
AB  - Most secondary structure prediction programs target only alpha helix and beta sheet structures and summarize all other structures in the random coil pseudo class. However, such an assignment often ignores existing local ordering in so-called random coil regions. Signatures for such ordering are distinct dihedral angle pattern. For this reason, we propose as an alternative approach to predict directly dihedral regions for each residue as this leads to a higher amount of structural information.We propose a multi-step support vector machine (SVM) procedure, dihedral prediction (DHPRED), to predict the dihedral angle state of residues from sequence. Trained on 20,000 residues our approach leads to dihedral region predictions, that in regions without alpha helices or beta sheets is higher than those from secondary structure prediction programs.DHPRED has been implemented as a web service, which academic researchers can access from our webpage http://www.fz-juelich.de/nic/cbb
KW  - Algorithms
KW  - Amino Acid Sequence
KW  - Artificial Intelligence
KW  - Computer Simulation
KW  - Models, Chemical
KW  - Models, Molecular
KW  - Molecular Sequence Data
KW  - Pattern Recognition, Automated: methods
KW  - Protein Structure, Secondary
KW  - Proteins: chemistry
KW  - Proteins: ultrastructure
KW  - Sequence Alignment: methods
KW  - Sequence Analysis, Protein: methods
KW  - Proteins (NLM Chemicals)
KW  - J (WoSType)
LB  - PUB:(DE-HGF)16
C6  - pmid:17005536
UR  - <Go to ISI:>//WOS:000242715200007
DO  - DOI:10.1093/bioinformatics/btl489
UR  - https://juser.fz-juelich.de/record/54190
ER  -