Invariant features for searching in protein fold databases

References

• Chou , K.-C. 2004 . Structural bioinformatics and its impact to biomedical science . Current Medicinal Chemistry , 11 : 2105 – 2134 .
   PubMed Web of Science ®Google Scholar
• Chou , K.-C. , Wei , D.-Q. , Du , Q.-S. , Sirois , S. and Zhong , W.-Z. 2006 . Progress in computational approach to drug development against SARS . Current Medicinal Chemistry , 13 : 3263 – 3270 .
   PubMed Web of Science ®Google Scholar
• Murzin , A. G. , Brenner , S. E. , Hubbard , T. and Chothia , C. 1995 . SCOP: a structural classification of proteins database for the investigation of sequences and structures . Journal of Molecular Biology , 247 : 536 – 540 .
   PubMed Web of Science ®Google Scholar
• Orengo , C. A. , Michie , A. D. , Jones , S. , Jones , D. T. , Swindells , M. B. and Thornton , J. M. 1997 . CATH – A hierarchic classification of protein domain structures . Structure , 5 ( 8 ) : 1093 – 1108 .
   PubMed Web of Science ®Google Scholar
• Holm , L. and Sander , C. 1998 . Touring protein fold space with Dali/FSSP . Nucleic Acids Research , 26 : 316 – 319 .
   PubMed Web of Science ®Google Scholar
• Shindyalov , I. N. and Bourne , P. E. 1998 . Protein structure alignment by incremental combinatorial extension (CE) of the optimal path . Protein Engineering , 11 : 739 – 747 .
   PubMedGoogle Scholar
• Carugo , O. and Pongor , S. 2002 . Protein fold similarity estimated by a probabilistic approach based on C α − C α distance comparison . Journal of Molecular Biology , 315 : 887 – 898 .
   PubMed Web of Science ®Google Scholar
• Huang , C. D. , Lin , C. T. and Pal , N. R. 2003 . Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification . IEEE Transactions on Nanobioscience , 2 ( 4 ) : 221 – 232 .
   PubMed Web of Science ®Google Scholar
• Røgen , P. and Fain , B. Automatic classification of protein structure by using Gauss integrals . Proceedings of the National Academy of Sciences of the United States of America . Vol. 100(1) , pp. 119 – 124 .
   Google Scholar
• Carugo , O. 2006 . Rapid methods for comparing protein structures ans scanning structure databases . Current Bioinformatics , 1 : 75 – 83 .
   Web of Science ®Google Scholar
• Lancia , G. , Carr , R. , Walenz , B. and Istrail , S. Optimal PDB structure alignments: A branch-and-cut algorithm for the maximum contact map overlap problem . Proceedings of 5th RECOMB, ACM Conference on Computational Molecular Biology . pp. 193 – 202 .
   Google Scholar
• Reisert , M. and Burkhardt , H. Irreducible group representation for 3D shape description . Proceedings of the DAGM'06 . Berlin, Germany. pp. 132 – 142 .
   Google Scholar
• Reisert , M. and Burkhardt , H. Invariant features for 3D-data based on group integration using directional information and spherical harmonic expansion . Proceedings of the ICPR'06 . Hong Kong.
   Google Scholar
• Burkhardt , H. and Siggelkow , H. 2001 . “ Invariant features in pattern recognition – fundamentals and applications ” . In Nonlinear Model-Based Image/Video Processing and Analysis , Edited by: Kotropoulos , C. and Pitas , I. 269 – 307 . New York : John Wiley .
   Google Scholar
• Haasdonk , B. , Halawani , A. and Burkhardt , H. Adjustable invariant features by partial Haar-integration . Proceedings of the 17th International Conference on Pattern Recognition (ICPR) . Vol. 2 , pp. 769 – 774 .
   Google Scholar
• Haasdonk , B. , Vossen , A. and Burkhardt , H. Invariance in kernel methods by Haar-integration kernels . Proceedings of the 14th Scandinavian Conference on Image Analysis . pp. 841 – 851 .
   Google Scholar
• Ronneberger , O. , Burkhardt , H. and Schultz , E. General-purpose object recognition in 3D volume data sets using gray-scale invariants . Proceedings of the International Conference on Pattern Recognition . Quebec, , Canada
   Google Scholar
• Ronneberger , O. , Fehr , J. and Burkhardt , H. Voxel-wise gray scale invariants for simultaneous segmentation and classification . Proceedings of the 27th DAGM Symposium . Vienna, Austria.
   Google Scholar
• Schael , M. 2002 . Invariant texture classification using group averaging with relational kernel functions . Texture 002, the 2nd international workshop on texture analysis and synthesis , : 129 – 134 .
   Google Scholar
• Siggelkow , S. , Schael , M. and Burkhardt , H. SIMBA – Search IMages By Appearance . Proceedings of the 23rd DAGM Symposium . pp. 9 – 16 .
   Google Scholar
• Setia , L. , Ick , J. and Burkhardt , H. SVM-based relevance feedback in image retrieval using invariant feature histograms . Proceedings of the IAPR Workshop on Machine Vision Applications . pp. 542 – 545 .
   Google Scholar
• Shamsuddin , S. M. , Sulaiman , M. N. and Darus , M. 2002 . Invarianceness of higher order centralised scaled-invariants undergo basic transformations result . International Journal of Computer Mathematics , 79 ( 1 ) : 39 – 48 .
   Web of Science ®Google Scholar
• Osada , R. , Funkhouser , T. , Chazelle , B. and Dobkin , D. 2001 . Matching 3D models with shape distribution . Proceedings Shape Modeling International ,
   Google Scholar
• Shilane , P. , Min , P. , Kazhdan , M. and Funkhouser , T. 2004 . “ The Princeton Shape Benchmark ” . In Shape Modeling International Genova, , Italy
   Google Scholar
• Berman , H. M. , Westbrook , J. , Feng , Z. , Gilliland , G. , Bhata , T. N. , Weissig , H. , Shindyalov , I. N. and Bourne , P. E. 2000 . The Protein Data Bank . Nucleic Acids Research , 28 : 235 – 242 .
   PubMed Web of Science ®Google Scholar