Table of Contents
1. Computational Studies of Protein Structure and Function Using Threading Program PROSPECT Dong Xu and Ying Xu 2. Bayesian Approach to Protein Fold Recognition: Building Protein Structural Models from Bits and Pieces Jadwiga Bienkowska, Hongxian He, Robert G. Rogers, Lihua Yu 3. Three-Dimensional Structure Prediction Using Simplified Structure Models and Bayesian Block Fragments Jun, ZhuRoland Luthy 4. Protein Structure Prediction Using Hidden Markov Model Structural Libraries Igor Tsigelny, Yuriy Sharikov, Lynn F. Ten Eyck 5. The Role of Sequence Information in Protein Structure Prediction Damien Devos, Florencio Pazos, Osvaldo Olmea, David de Juan, Osvaldo Grana, Jose M. Fernandez, Alfonso Valencia 6. Protein Fold Recognition and Comparative Modeling Using HOMSTRAD, JOY, and FUGUE Ricardo Nunez Miguel, Jiye Shi, Kenji Mizuguchi 7. Fully Automated Protein Tertiary Structure Prediction Using Fourier Transform Spectral Methods Carlos Adriel Del Carpio Munoz and Atsushi Yoshimori 8. From the Building Blocks Folding Model to Protein Structure Prediction Nurit Haspel, C-J Tsai, Haim Wolfson, Ruth Nussinov 9. Protein Threading Statistics: An Attempt to Assess the Significance of a Fold Assignment to a Sequence Antoine Marin, Joel Pothier, Karel Zimmermann, and Jean-Francois Gibrat 10. Protein Structure Prediction by Threading: Force Field Philosophy, Approaches to Alignment Thomas Huber, Andrew Torda 11. Predicting Protein Structure Using SAM, UCSC's Hidden Markov Model Tools Kevin Karplus 12. Local Genome Organization, Gene Expression, and Structural Genomics: Evolution at Work Wayne Volkmuth, Nickolai Alexandrov 13. Protein Structure Prediction on the Basis of Combinatorial Peptide Library Screening I Tsigelny, Y Sharikov, M Kelner, L Ten Eyck 14. A User's Guide to Fold Recognition Naomi Siew, Daniel Fischer 15. Structure Prediction Meta Server Leszek Rychlewski 16. Improved Fold Recognition by Using the PCONS Consensus Approach Huisheng Fang, Bjorn Wallin, Jesper Lundstrom, Christer von Wowern, and Arne Elofsson 17. New Insights into Protein Fold Space and Sequence-Structure Relationships Ilya N. Shindyalov and Philip E. Bourne 18. A Flexible Method for Structural Alignment in Structure Prediction Assessments Vladimir Kotlovyi, Igor Tsigelny, Lynn Ten Eyck 19. Comparative Analysis of Protein Structure: New Concepts and Approaches for Multiple Structure Alignment Chittibabu Guda, Eric D. Scheeff, Philip E. Bourne, and Ilya N. Shindyalov 20. Comparative Analysis of Protein Structure: Automated vs. Manual Alignment of the Protein Kinase Family Eric D. Scheeff, Philip E. Bourne, and Ilya N. Shindyalov
Igor F. Tsigelny, Ph.D., is well-known scientist working for many years in the fields of bioinfomatics, molecular modeling, and theoretical drug design. He works in the University of California at San Diego and San Diego Supercomputer Center. His index of citations is about 1000.
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