A Review of Evolutionary Algorithms for Computing Functional Conformations of Protein Molecules
暂无分享,去创建一个
[1] A. D. McLachlan,et al. A mathematical procedure for superimposing atomic coordinates of proteins , 1972 .
[2] C. Anfinsen. Principles that govern the folding of protein chains. , 1973, Science.
[3] K. Dejong,et al. An analysis of the behavior of a class of genetic adaptive systems , 1975 .
[4] N. Go,et al. Studies on protein folding, unfolding and fluctuations by computer simulation. I. The effect of specific amino acid sequence represented by specific inter-unit interactions. , 2009 .
[5] Kenneth Alan De Jong,et al. An analysis of the behavior of a class of genetic adaptive systems. , 1975 .
[6] M. Karplus,et al. CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .
[7] H. Scheraga,et al. Monte Carlo-minimization approach to the multiple-minima problem in protein folding. , 1987, Proceedings of the National Academy of Sciences of the United States of America.
[8] Kalyanmoy Deb,et al. An Investigation of Niche and Species Formation in Genetic Function Optimization , 1989, ICGA.
[9] Akbar Nayeem,et al. A comparative study of the simulated‐annealing and Monte Carlo‐with‐minimization approaches to the minimum‐energy structures of polypeptides: [Met]‐enkephalin , 1991 .
[10] R. Unger,et al. Finding the lowest free energy conformation of a protein is an NP-hard problem: proof and implications. , 1993, Bulletin of mathematical biology.
[11] M. Levitt,et al. Exploring conformational space with a simple lattice model for protein structure. , 1994, Journal of molecular biology.
[12] J. Skolnick,et al. Monte carlo simulations of protein folding. I. Lattice model and interaction scheme , 1994, Proteins.
[13] R. Abagyan,et al. Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins. , 1994, Journal of molecular biology.
[14] Ruben Abagyan,et al. ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation , 1994, J. Comput. Chem..
[15] A. Brünger,et al. Torsion angle dynamics: Reduced variable conformational sampling enhances crystallographic structure refinement , 1994, Proteins.
[16] David B. Fogel,et al. Evolutionary computation - toward a new philosophy of machine intelligence (3. ed.) , 1995 .
[17] D. Yee,et al. Principles of protein folding — A perspective from simple exact models , 1995, Protein science : a publication of the Protein Society.
[18] M. Levitt,et al. The complexity and accuracy of discrete state models of protein structure. , 1995, Journal of molecular biology.
[19] D Baker,et al. Global properties of the mapping between local amino acid sequence and local structure in proteins. , 1996, Proceedings of the National Academy of Sciences of the United States of America.
[20] A V Finkelstein,et al. Adjusting potential energy functions for lattice models of chain molecules , 1996, Proteins.
[21] K Schulten,et al. VMD: visual molecular dynamics. , 1996, Journal of molecular graphics.
[22] J. Onuchic,et al. Theory of protein folding: the energy landscape perspective. , 1997, Annual review of physical chemistry.
[23] J. Doye,et al. Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms , 1997, cond-mat/9803344.
[24] William E. Hart,et al. Robust Proofs of NP-Hardness for Protein Folding: General Lattices and Energy Potentials , 1997, J. Comput. Biol..
[25] K. Dill,et al. From Levinthal to pathways to funnels , 1997, Nature Structural Biology.
[26] Thomas Bäck,et al. Evolutionary computation: Toward a new philosophy of machine intelligence , 1997, Complex..
[27] A T Brünger,et al. Torsion-angle molecular dynamics as a new efficient tool for NMR structure calculation. , 1997, Journal of magnetic resonance.
[28] Mihalis Yannakakis,et al. On the Complexity of Protein Folding , 1998, J. Comput. Biol..
[29] William M. Spears,et al. Simple Subpopulation Schemes , 1998 .
[30] Kalyanmoy Deb,et al. A Niched-Penalty Approach for Constraint Handling in Genetic Algorithms , 1999, ICANNGA.
[31] D. Borchelt,et al. Variation in the biochemical/biophysical properties of mutant superoxide dismutase 1 enzymes and the rate of disease progression in familial amyotrophic lateral sclerosis kindreds. , 1999, Human molecular genetics.
[32] K Yue,et al. Predicting the structures of 18 peptides using Geocore , 1999, Protein science : a publication of the Protein Society.
[33] N. Krasnogor,et al. A Memetic Algorithm With Self-Adaptive Local Search: TSP as a case study , 2000, GECCO.
[34] Helena Ramalhinho Dias Lourenço,et al. Iterated Local Search , 2001, Handbook of Metaheuristics.
[35] Ming Zhang,et al. A New Method for Fast and Accurate Derivation of Molecular Conformations , 2002, J. Chem. Inf. Comput. Sci..
[36] KalyanmoyDebandSamirAgrawal KanpurGeneticAlgorithmsLaboratory,et al. A Niched-Penalty Approach for Constraint Handling in Genetic Algorithms , 2002 .
[37] David J. Wales,et al. Energy landscapes of model polyalanines , 2002 .
[38] Gary B. Lamont,et al. Solving the Protein Structure Prediction Problem Through a Multiobjective Genetic Algorithm , 2002 .
[39] Edmund K. Burke,et al. Multimeme Algorithms for Protein Structure Prediction , 2002, PPSN.
[40] Alan F. Scott,et al. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders , 2002, Nucleic Acids Res..
[41] David Corne,et al. An Introduction to Bioinformatics for Computer Scientists , 2003 .
[42] Sue Whitesides,et al. A complete and effective move set for simplified protein folding , 2003, RECOMB '03.
[43] José R. Álvarez,et al. Artificial Neural Nets Problem Solving Methods , 2003, Lecture Notes in Computer Science.
[44] David W. Corne,et al. Use of a novel Hill-climbing genetic algorithm in protein folding simulations , 2003, Comput. Biol. Chem..
[45] Jim Smith,et al. Protein structure prediction with co-evolving memetic algorithms , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[46] John A Tainer,et al. ALS mutants of human superoxide dismutase form fibrous aggregates via framework destabilization. , 2003, Journal of molecular biology.
[47] Claudio Soto,et al. Unfolding the role of protein misfolding in neurodegenerative diseases , 2003, Nature Reviews Neuroscience.
[48] Haruki Nakamura,et al. Announcing the worldwide Protein Data Bank , 2003, Nature Structural Biology.
[49] Carlos Cotta,et al. Protein Structure Prediction Using Evolutionary Algorithms Hybridized with Backtracking , 2009, IWANN.
[50] Ron Unger. The Genetic Algorithm Approach to Protein Structure Prediction , 2004 .
[51] J. Onuchic,et al. Theory of Protein Folding This Review Comes from a Themed Issue on Folding and Binding Edited Basic Concepts Perfect Funnel Landscapes and Common Features of Folding Mechanisms , 2022 .
[52] Andrea Tettamanzi,et al. A Memetic Algorithm for Protein Structure Prediction in a 3D-Lattice HP Model , 2004, EvoWorkshops.
[53] Andy J. Keane,et al. Meta-Lamarckian learning in memetic algorithms , 2004, IEEE Transactions on Evolutionary Computation.
[54] Masao Iwamatsu,et al. Basin hopping with occasional jumping , 2004 .
[55] David Baker,et al. Protein Structure Prediction Using Rosetta , 2004, Numerical Computer Methods, Part D.
[56] Charles L. Brooks,et al. Application of torsion angle molecular dynamics for efficient sampling of protein conformations , 2005, J. Comput. Chem..
[57] Heitor Silvério Lopes,et al. An Enhanced Genetic Algorithm for Protein Structure Prediction Using the 2D Hydrophobic-Polar Model , 2005, Artificial Evolution.
[58] P. Bradley,et al. Toward High-Resolution de Novo Structure Prediction for Small Proteins , 2005, Science.
[59] V. Cutello,et al. A multi-objective evolutionary approach to the protein structure prediction problem , 2006, Journal of The Royal Society Interface.
[60] Jim Smith,et al. The Co-Evolution of Memetic Algorithms for Protein Structure Prediction , 2005 .
[61] Vincenzo Cutello,et al. A Class of Pareto Archived Evolution Strategy Algorithms Using Immune Inspired Operators for Ab-Initio Protein Structure Prediction , 2005, EvoWorkshops.
[62] A. Schug,et al. Basin hopping simulations for all-atom protein folding. , 2006, The Journal of chemical physics.
[63] Madhu Chetty,et al. A Guided Genetic Algorithm for Protein Folding Prediction Using 3D Hydrophobic-Hydrophilic Model , 2006, 2006 IEEE International Conference on Evolutionary Computation.
[64] Kevin Kok Wai Wong,et al. Classification of adaptive memetic algorithms: a comparative study , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[65] Kenneth DeJong. Evolutionary computation: a unified approach , 2007, GECCO.
[66] Colin R. Reeves,et al. Evolutionary computation: a unified approach , 2007, Genetic Programming and Evolvable Machines.
[67] Hisao Ishibuchi,et al. Special Issue on Memetic Algorithms , 2007, IEEE Trans. Syst. Man Cybern. Part B.
[68] Joshua D. Knowles,et al. Investigations into the Effect of Multiobjectivization in Protein Structure Prediction , 2008, PPSN.
[69] Claudio Soto,et al. Protein misfolding and neurodegeneration. , 2008, Archives of neurology.
[70] Peter G Wolynes,et al. Protein structure prediction using basin-hopping. , 2008, The Journal of chemical physics.
[71] Hans-Joachim Böckenhauer,et al. A Local Move Set for Protein Folding in Triangular Lattice Models , 2008, WABI.
[72] El-Ghazali Talbi,et al. A grid-based genetic algorithm combined with an adaptive simulated annealing for protein structure prediction , 2008, Soft Comput..
[73] Oliver Brock,et al. Guiding conformation space search with an all‐atom energy potential , 2008, Proteins.
[74] William E. Hart,et al. Recent Advances in Memetic Algorithms , 2008 .
[75] Mireille Avigal,et al. Genetic algorithms with local search optimization for protein structure prediction problem , 2008, GECCO '08.
[76] D. Boehr,et al. How Do Proteins Interact? , 2008, Science.
[77] K. Dill,et al. The protein folding problem. , 1993, Annual review of biophysics.
[78] Cecilia Clementi,et al. Coarse-grained models of protein folding: toy models or predictive tools? , 2008, Current opinion in structural biology.
[79] Julio Ortega Lopera,et al. Parallel Protein Structure Prediction by Multiobjective Optimization , 2009, 2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing.
[80] Madhu Chetty,et al. Novel Memetic Algorithm for Protein Structure Prediction , 2009, Australasian Conference on Artificial Intelligence.
[81] L. Kavraki,et al. Multiscale characterization of protein conformational ensembles , 2009, Proteins.
[82] Ting Wang,et al. 3D Protein structure prediction with genetic tabu search algorithm , 2009, 2009 Second International Symposium on Knowledge Acquisition and Modeling.
[83] Abdul Sattar,et al. Genetic Algorithm inAb Initio Protein Structure Prediction Using Low Resolution Model: A Review , 2009, Biomedical Data and Applications.
[84] Vladimir N Uversky,et al. Intrinsic disorder in proteins associated with neurodegenerative diseases. , 2009, Frontiers in bioscience.
[85] R. Rosenfeld. Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.
[86] Hisao Ishibuchi,et al. Special issue on emerging trends in soft computing: memetic algorithms , 2009, Soft Comput..
[87] Julio Ortega Lopera,et al. Comparison of parallel multi-objective approaches to protein structure prediction , 2011, The Journal of Supercomputing.
[88] Michael Levitt,et al. Generalized ensemble methods for de novo structure prediction , 2009, Proceedings of the National Academy of Sciences.
[89] James E. Fitzgerald,et al. Mimicking the folding pathway to improve homology-free protein structure prediction , 2009, Proceedings of the National Academy of Sciences.
[90] R. Nussinov,et al. The role of dynamic conformational ensembles in biomolecular recognition. , 2009, Nature chemical biology.
[91] Zhihong He,et al. Protein folding simulations of 2D HP model by the genetic algorithm based on optimal secondary structures , 2010, Comput. Biol. Chem..
[92] David Becerra,et al. A parallel multi-objective ab initio approach for protein structure prediction , 2010, 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
[93] Amarda Shehu,et al. Guiding the Search for Native-like Protein Conformations with an Ab-initio Tree-based Exploration , 2010, Int. J. Robotics Res..
[94] Dumitru Dumitrescu,et al. An Evolutionary Model Based on Hill-Climbing Search Operators for Protein Structure Prediction , 2010, EvoBIO.
[95] Giuseppe Nicosia,et al. Robust Bio-active Peptide Prediction Using Multi-objective Optimization , 2010, 2010 International Conference on Biosciences.
[96] Erick Fredj,et al. A new hybrid algorithm for finding the lowest minima of potential surfaces: Approach and application to peptides , 2011, J. Comput. Chem..
[97] Pascal Van Hentenryck,et al. On Lattice Protein Structure Prediction Revisited , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[98] Amarda Shehu,et al. Populating Local Minima in the Protein Conformational Space , 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine.
[99] Jyh-Jong Tsay,et al. Ab initio protein structure prediction based on memetic algorithm and 3D FCC lattice model , 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).
[100] C. Dobson,et al. Protein Dynamics: Moore's Law in Molecular Biology , 2011, Current Biology.
[101] Jens Meiler,et al. ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. , 2011, Methods in enzymology.
[102] Julio Ortega Lopera,et al. PITAGORAS-PSP: Including domain knowledge in a multi-objective approach for protein structure prediction , 2011, Neurocomputing.
[103] R. Dror,et al. How Fast-Folding Proteins Fold , 2011, Science.
[104] Andrew Lewis,et al. Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[105] Dumitru Dumitrescu,et al. Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction , 2011, BioData Mining.
[106] Camelia Chira,et al. A hybrid evolutionary approach to protein structure prediction with lattice models , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[107] Cheng-Jian Lin,et al. An effective hybrid of hill climbing and genetic algorithm for 2D triangular protein structure prediction , 2011, Proteome Science.
[108] Abdul Sattar,et al. Memory-based local search for simplified protein structure prediction , 2012, BCB.
[109] Michele Vendruscolo,et al. Structure of an Intermediate State in Protein Folding and Aggregation , 2012, Science.
[110] Amarda Shehu,et al. Evolutionary-inspired probabilistic search for enhancing sampling of local minima in the protein energy surface , 2012, Proteome Science.
[111] Gregorio Toscano Pulido,et al. Locality-based multiobjectivization for the HP model of protein structure prediction , 2012, GECCO '12.
[112] Kenneth A. De Jong,et al. A Spatial EA Framework for Parallelizing Machine Learning Methods , 2012, PPSN.
[113] Richard O. Day,et al. A Multiobjective Approach Applied to the Protein Structure Prediction Problem , 2012 .
[114] Rosni Abdullah,et al. A hybrid harmony search algorithm for ab initio protein tertiary structure prediction , 2012, Network Modeling Analysis in Health Informatics and Bioinformatics.
[115] Gregorio Toscano Pulido,et al. Multiobjectivizing the HP Model for Protein Structure Prediction , 2012, EvoCOP.
[116] David Baker,et al. The dual role of fragments in fragment‐assembly methods for de novo protein structure prediction , 2012, Proteins.
[117] Kam Y. J. Zhang,et al. A Probabilistic Fragment-Based Protein Structure Prediction Algorithm , 2012, PloS one.
[118] Amarda Shehu,et al. Efficient basin hopping in the protein energy surface , 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine.
[119] Amarda Shehu,et al. A population-based evolutionary algorithm for sampling minima in the protein energy surface , 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops.
[120] Amarda Shehu,et al. Basin Hopping as a General and Versatile Optimization Framework for the Characterization of Biological Macromolecules , 2012, Adv. Artif. Intell..
[121] Gang Li,et al. Heuristic-based tabu search algorithm for folding two-dimensional AB off-lattice model proteins , 2013, Comput. Biol. Chem..
[122] K. Lindorff-Larsen,et al. Atomic-level description of ubiquitin folding , 2013, Proceedings of the National Academy of Sciences.
[123] Amarda Shehu,et al. Rapid sampling of local minima in protein energy surface and effective reduction through a multi-objective filter , 2013, Proteome Science.
[124] Jyh-Jong Tsay,et al. An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets , 2013, Proteome Science.
[125] Amarda Shehu,et al. A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction , 2013, BMC Structural Biology.
[126] Kenneth A. De Jong,et al. Off-lattice protein structure prediction with homologous crossover , 2013, GECCO '13.
[127] Amarda Shehu,et al. Multi-Objective Stochastic Search for Sampling Local Minima in the Protein Energy Surface , 2013, BCB.
[128] Takeo Kanade,et al. Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics , 2013, Lecture Notes in Computer Science.
[129] Brian S. Olson,et al. Evolving local minima in the protein energy surface , 2013 .
[130] Qiang Zhang,et al. Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model , 2013, Journal of Molecular Modeling.
[131] Sara Reardon. Large NIH projects cut , 2013, Nature.
[132] Amarda Shehu,et al. Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method , 2013, BMC Structural Biology.
[133] P. Stenson,et al. The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine , 2013, Human Genetics.
[134] Yang Zhang. Interplay of I‐TASSER and QUARK for template‐based and ab initio protein structure prediction in CASP10 , 2014, Proteins.
[135] Amarda Shehu,et al. A multiscale hybrid evolutionary algorithm to obtain sample-based representations of multi-basin protein energy landscapes , 2014, BCB.
[136] Qiang Zhang,et al. Improved hybrid optimization algorithm for 3D protein structure prediction , 2014, Journal of Molecular Modeling.
[137] Rommie E Amaro,et al. Editorial overview: Theory and simulation: Tools for solving the insolvable. , 2014, Current opinion in structural biology.
[138] Brian S. Olson,et al. Multi-Objective Optimization Techniques for Conformational Sampling in Template-Free Protein Structure Prediction , 2014 .
[139] Kenneth A. De Jong,et al. Evolution Strategies for Exploring Protein Energy Landscapes , 2015, GECCO.
[140] R. Nussinov,et al. Allosteric effects of the oncogenic RasQ61L mutant on Raf-RBD. , 2015, Structure.
[141] Amarda Shehu,et al. A Data-Driven Evolutionary Algorithm for Mapping Multibasin Protein Energy Landscapes , 2015, J. Comput. Biol..
[142] Ruth Nussinov,et al. Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm , 2015, PLoS Comput. Biol..
[143] Kenneth A. De Jong,et al. Mapping Multiple Minima in Protein Energy Landscapes with Evolutionary Algorithms , 2015, GECCO.