• Detailed information on the project can be found here:
  
  • Automated Grid-Aware, three-tier, Protocol for Protein Structure Comparison
  • Next Generation Decision Support: Automating the Heuristic Design Process
• The project has been funded by:
  
  • Biotechnology and Biological Sciences Research Council (BBSRC), UK.
    Grant Number: BB/C511764/1
  • Engineering and Physical Sciences Research Council (EPSRC),UK.
    Grant Number: EP/D061571/1
• The main developers in this project are (in alphabetical order):
  
  • Daniel Barthel, School of Computer Science, University of Nottingham, UK.
  • Natalio Krasnogor, School of Computer Science, University of Nottingham, UK.
  • Azhar Ali Shah, School of Computer Science, University of Nottingham, UK.
  • Paweł Widera, School of Computer Science, University of Nottingham, UK.
• The main external collaborators in this project are (in alphabetical order):
  
  • Fabian Birzele, Department of Computer Science, University of Munich, Germany.
  • Jacek Blazewicz, Institute of Computing Science, Poznan University of Technology, Poland.
  • Jonathan D. Hirst, School of Chemistry, University of Nottingham, UK.
  • Robert Hoffman, Computational Biology Center (cBIO), New York, USA.
  • Michal Linial, Hebrew University, Jerusalem, Israel.
  • David A. Pelta, University of Granada, Spain.
  • Alfonso Valencia, Centro Nacional de Biotecnologia, Madrid, Spain.

1. Main References: ProCKSI
   ProCKSI: a decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information
   D. Barthel, J.D. Hirst, J. Blazewicz, E.K. Burke and N. Krasnogor, BMC Bioinformatics, 8, 416, 2007.
2. Similarity Comparison Method: USM
   Measuring the Similarity of Protein Structures by Means of the Universal Similarity Metric
   N. Krasnogor and D. A. Pelta. Bioinformatics 20(7), 1015-1021, 2004.
3. Similarity Comparison Method: MaxCMO
   A simple and fast heuristic for protein structure comparison
   D. A. Pelta, J. R. Gonzalez, M. Moreno Vega. BMC Bioinformatics 9, 161, 2008.
4. Similarity Comparison Method: DaliLite
   DaliLite workbench for protein structure comparison
   L. Holm and J. Park, Bioinformatics 16, 566-567, 2000.
5. Similarity Comparison Method: CE
   Protein structure alignment by incremental combinatorial extension (CE) of the optimal path
   I. N. Shindyalov and P. E. Bourne, Protein Engineering 11, 739-747, 1998.
6. Similarity Comparison Method: TM-align
   TM-align: A protein structure alignment algorithm based on TM-score
   Y. Zhang and J. Skolnick, Nucleic Acids Research 33, 2302-2309, 2005.
7. Similarity Comparison Method: FAST
   FAST: A Novel Protein Structure Alignment Algorithm
   J. Zhu and Y. Weng, Proteins: Structure, Function and Bioinformatics 14, 417-423, 2005.
8. Similarity Comparison Method: Vorolign
   Vorolign - Fast Structural Alignment using Voronoi Contacts
   F. Birzele, J. E. Gewehr, G. Csaba and R. Zimmer, Bioinformatics 23, e205-e211, 2007.
9. Additional Source of Information: PDB
   The Protein Data Bank
   H. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. Bhat, H. Weissig, I. Shindyalov, P. Bourne, Nucleic Acids Res. 28, 235–242, 2000.
10. Additional Source of Information: CATH
    CATH - A Hierarchic Classification of Protein Domain Structures
    C.A. Orengo, A.D. Michie, S. Jones, D.T. Jones, M.B. Swindells, J.M. Thornton, Structure 5, 1093–1108, 1997.
11. Additional Source of Information: SCOP
    SCOP: a Structural Classification of Proteins database
    T.J. Hubbard, B. Ailey, S.E. Brenner, A.G. Murzin, C. Chothia, Nucleic Acids Research 27, 254–256, 1999.
12. Additional Source of Information: iHOP
    A Gene Network for Navigating the Literature
    R. Hoffmann and A. Valencia, Nature Genetics 36, 664-664, 2004.
13. Analysis and Visualisation Tools: Hierarchical Tree Visualisation
    Visualizing large hierarchical clusters in hyperbolic space
    J. Bingham, S. Sudarsanam, Bioinformatics 16(7), 660-661, 2000.
14. Analysis and Visualisation Tools: Protein Structure Images
    MOLSCRIPT: A Program to Produce Both Detailed and Schematic Plots of Protein Structures
    Per J. Kraulis, J. Appl. Cryst. 24, 946-950, 1991.
15. Analysis and Visualisation Tools: Clustering
    QCLUST V0.2 John Brzustowski, University of Alberta, United States of America.

• ProCKSI integrates the following similarity comparison methods:
  • Universal Similarity Metric (USM) using Kolmogorov Complexity with contact maps
  • Maximum Contact Map Overlap (MaxCMO, 1.0) using a Variable Neighbourhood Search with contact maps
  • DaliLite (2.4.4) using distance matrices
  • Combinatorial Extension (CE, 1.0.2) of the optimal path
  • TM-align (16/10/2007) using Dynamic Programming with TM-score rotation matrices
  • FAST Alignment and Search Tool (FAST, 22/02/2004) using an elimination heuristic
  • Vorolign (1.0) using Voronoi contacts
• ProCKSI links to the following external resources as to provide further information:
  • PDB repository
  • CATH structural classification database
  • SCOP structural classification database
  • iHOP providing direct links to related scientific literature
• Further software used by ProCKSI:
  • ParsePDB (2.0) by B. Bulheller for parsing PDB files
  • MolScript (2.1.2) by P. Kraulis for generating images from PDB files
  • Raster3D (2.7d) by E.A. Merritt and D.J. Bacon for rendering high-quality images
  • qclust (0.2) by John Brzustowski for hierarchically clustering
  • HyperTree (V1) viewer visualising the hierarchical tree, being kindly allowed to distribute it

• Benjamin Bulheller, School of Chemistry, University of Nottingham, UK.
• Juan Ramón Gonzalez Gonzalez, University of Granada, Spain.
• Zhelong Jin, School of Computer Science, University of Notingham, UK.

• Corporate Design: Daniel Barthel, Paweł Widera
• Logo: Benjamin Bulheller, Daniel Barthel, Jaume Baccardit, Itziar Frades

Last but not least, we would like to thank the Technical Service Group of the School of Computer Science for their assistance. These are especially Nick Reynolds, William Armitage and Viktor Huddleston.