Genetic Algorithms and Their Use in Chemistry

Reviews in Computational Chemistry

Volumn 10, Issue , 1997, Pages 1-73

  Judson, Richard ^a  

^a SANDIA NATIONAL LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CURVE FITTING; GENETIC ALGORITHMS;

ENERGY FUNCTIONS; PROTEIN SEQUENCES; SPECTRAL CURVES; VALUE ESTIMATION;

BIOINFORMATICS;

EID: 0031501455     PISSN: 10693599     EISSN: None     Source Type: Book Series    
DOI: None     Document Type: Article

References (151)

1. T. Schlick, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1992, Vol. 3, pp. 1-71. Optimization Methods in Computational Chemistry.
2. C. Darwin, The Origin of Species, 6th edit., P. F. Collier and Sons, New York, 1909.
3. E. Mayr, Introduction to Darwin's "Origin of Species," Harvard University Press, Cambridge, MA, 1964.
4. N. Eldredge, Reinventing Darwin - The Great Debate at the High Table of Evolutionary Theory, Wiley, New York, 1995.
5. J. H. Holland, Sci. Am., 267, July 1992, p. 66. Genetic Algorithms.
6. J. H. Holland, Adaptation in Natural and Artificial Systems, MIT Press, Cambridge, MA, 1992.
7. I. Rechenberg, Evolutionsstrategie - Optimierung Technischer Systeme nach Prinzipien der Biologischen Evolution, Frommann-Holzboog, Stuttgart, 1973.
8. C. Brandon and J. Tooze, Introduction to Protein Structure, Garland, New York, 1991.
9. D. Goldberg, Genetic Algorithms in Search, Optimization, and Learning, Addison-Wesley, Reading, MA, 1989.
10. K. A. Dejong, Doctoral Thesis, University of Michigan, 1976. An Analysis of the Behavior of a Class of Genetic Adaptive Systems.
11. D. E. Goldberg, K. Deb, and J. H. Clark, Complex Systems, 6, 333 (1992). Genetic Algorithms, Noise, and the Sizing of Populations.
12. J. Koza, Genetic Programming, MIT Press, Cambridge, MA, 1992.
13. G. J. E. Rawlins, Ed., Foundations of Genetic Algorithms, Morgan Kaufmann, San Mateo, CA, 1991.
14. R. K. Belew and L. B. Booker, Eds., Proceedings of the Fourth International Conference on Genetic Algorithms, Morgan Kauf man, San Mateo, CA, 1991.
15. R. S. Judson, E. P. Jaeger, A. M. Treasurywala, and M. L. Peterson, J. Comput. Chem., 14, 1407 (1993). Conformational Searching Methods for Small Molecules. II. Genetic Algorithm Approach.
16. J. E. Baker, in Proceedings of an International Conference on Genetic Algorithms and Their Applications, J. Greffenstette, Ed., Lawrence Erlbaum Associates, Cambridge, MA, 1985, pp. 101-111. Adaptive Selection Methods for Genetic Algorithms.
17. H. Mühlenbein, in Foundations of Genetic Algorithms, G. J. E. Rawlins, Ed., Morgan Kaufman, San Mateo, CA, 1991, 316 pp. Evolution in Time and Space - The Parallel Genetic Algorithm.
18. H. Mühienbein, M. Schomisch, and J. Born, Parall. Computing, 17, 619 (1991). A Parallel Genetic Algorithm as Function Optimizer.
19. L. Davis, Handbook of Genetic Algorithms, Van Nostrand Reinhold, New York, 1991.
20. G. Syswerda, in Proceedings of the Third International Conference on Genetic Algorithms, J. D. Schaffer, Ed., Morgan Kaufmann, San Mateo, CA, 1989, pp. 2-9. Uniform Crossover in Genetic Algorithms.
21. D. E. Goldberg and J. Richardson, in Genetic Algorithms and Their Applications: Proceedings of the Second International Conference on Genetic Algorithms, J. Greffenstette, Ed., Lawrence Erlbaum Associates, Cambridge, MA, 1987, pp. 41-49. Genetic Algorithms and Sharing for Multimodal Function Optimization.
22. R. S. Judson, J. Phys. Chem., 96, 10102 (1992). Teaching Polymers to Fold.
23. D. E. Goldberg, K. Deb, and B. Korb, in Proceedings of the Fourth International Conference on Genetic Algorithms, R. K. Belew and L. B. Booker, Eds., Morgan Kaufmann, San Mateo, CA, 1993, pp. 24-30. Don't Worry, Be Messy. D. E. Goldberg, K. Deb, H. Kargupta, and G. Harik, University of Illinois at Urbana-Champaign, Department of General Engineering, Illinois Genetic Algorithms Laboratory, Report No. 93004, 1993. Rapid, Accurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms.
24. D. E. Goldberg, K. Deb, and B. Korb, in Proceedings of the Fourth International Conference on Genetic Algorithms, R. K. Belew and L. B. Booker, Eds., Morgan Kaufmann, San Mateo, CA, 1993, pp. 24-30. Don't Worry, Be Messy. D. E. Goldberg, K. Deb, H. Kargupta, and G. Harik, University of Illinois at Urbana-Champaign, Department of General Engineering, Illinois Genetic Algorithms Laboratory, Report No. 93004, 1993. Rapid, Accurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms.
25. D. E. Goldberg, Complex Systems, 5, 139 (1991). Real-Coded Genetic Algorithms, Virtual Alphabets, and Blocking.
26. R. S. Judson, M. E. Colvin, J. C. Meza, A. Huffer, and D. Gutierrez, Int. J. Quantum Chem., 44, 277 (1992). Do Intelligent Configuration Search Techniques Outperform Random Search for Large Molecules?
27. R. S. Judson and H. Rabitz, Phys. Rev. Lett., 68, 1500 (1992). Teaching Lasers to Control Molecules.
28. R. A. Kendall, R. J. Harrison, R. J. Littlefield, and M. F. Guest, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1995, Vol. 6, pp. 209-316. High Performance Computing in Computational Chemistry: Methods and Machines.
29. T. Bäck, F. Hoffmeister, and H.-P. Schwefel, in Proceedings of the Fourth International Conference on Genetic Algorithms, R. K. Belew and L. B. Booker, Eds., Morgan Kaufmann, San Mateo, CA, 1991, pp. 2-9. A Survey of Evolutionary Strategies. T. Bäck and H.-P. Schwefel, Evolutionary Computation, 1, 1 (1993). An Overview of Evolutionary Algorithms for Parameter Optimization.
30. T. Bäck, F. Hoffmeister, and H.-P. Schwefel, in Proceedings of the Fourth International Conference on Genetic Algorithms, R. K. Belew and L. B. Booker, Eds., Morgan Kaufmann, San Mateo, CA, 1991, pp. 2-9. A Survey of Evolutionary Strategies. T. Bäck and H.-P. Schwefel, Evolutionary Computation, 1, 1 (1993). An Overview of Evolutionary Algorithms for Parameter Optimization.
31. K. Sigmund, Games of Life, Explorations in Ecology, Evolution, and Culture, Oxford University Press, Oxford, U.K., 1993.
32. M. Singer and P. Berg, Genes and Genomes, A Changing Perspective, University Science Books, Mill Valley, CA, 1991.
33. C. L. Karr, S. K. Sharma, W. Hatcher, and T. R. Harper, in Modeling and Simulation of the Control Hydrometallic Processes, Proceedings of an International Symposium, V. G. Papangelakis and G. P. Demopoulos, Eds., Canadian Institute of Mining, Metallurgy, and Petrology, Montreal, 1993, pp. 227-236. Fuzzy Logic and Genetic Algorithms for the Control of Exothermic Chemical Reactions.
34. I. P. Androulakis and V. Venkatasubramanian, Comput. Chem. Eng., 15, 217 (1991). A Genetic Algorithm Framework For Process Design and Optimization.
35. D. B. Hibbert, Chemometrics Intell. Lab. Syst., 19, 277 (1993). Genetic Algorithms in Chemistry.
36. C. B. Lucasius and G. Kateman, Chemometrics Intell. Lab. Syst., 19, 1 (1993). Understanding and Using Genetic Algorithms. Part 1. Concepts, Properties and Context.
37. Y. Xiao and D. E. Williams, Chem. Phys. Lett., 215, 17 (1993). Genetic Algorithm: A New Approach to the Prediction of the Structure of Molecular Clusters.
38. Y. Xiao and D. E. Williams, Comput. Chem., 18, 199 (1994). GAME: Genetic Algorithm for Minimization of Energy: An Interactive Program for Three Dimensional Intermolecular Interactions.
39. B. Hartke, J. Phys. Chem., 97, 9973 (1993). Global Geometry Optimization of Clusters Using Genetic Algorithms.
40. R. W. Smith, Comput. Phys. Commun., 71, 134 (1992). Energy Minimization in Binary Alloys via Genetic Algorithms.
41. J. Mestres and G. E. Scuseria, J. Comput. Chem., 16, 729 (1995). Genetic Algorithms: A Robust Scheme for Geometry Optimizations and Global Minimum Structure Problems.
42. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C, 2nd edit., Cambridge University Press, Cambridge, U.K., 1992, pp. 408-412.
43. J. C. Meza and M. L. Martinez, J. Comput. Chem., 15, 627 (1994). Direct Search Methods for the Molecular Conformation Problem. J. C. Meza, R. S. Judson, T. R. Faulkner, and A. M. Treasurywala, J. Comput. Chem., 17, 1142 (1996). A Comparison of a Direct Search Method and a Genetic Algorithm for Conformational Searching.
44. J. C. Meza and M. L. Martinez, J. Comput. Chem., 15, 627 (1994). Direct Search Methods for the Molecular Conformation Problem. J. C. Meza, R. S. Judson, T. R. Faulkner, and A. M. Treasurywala, J. Comput. Chem., 17, 1142 (1996). A Comparison of a Direct Search Method and a Genetic Algorithm for Conformational Searching.
45. J. J. Grefenstette and N. N. Schraudolph, Naval Research Laboratory, Washington, D.C., 1990. GENESIS 1.2ucsd.
46. F. Mohamadi, N. J. G. Richards, W. G. Guida, R. Liskamp, M. Lipton, C. Caufield, G. Chang, T. Hendrickson, and W. C. Still, J. Comput. Chem., 11, 440 (1990). Macro-Model - An Integrated Software System for Modeling Organic and Bioinorganic Molecules Using Molecular Mechanics.
47. R. A. Dammkoehler, S. F. Karasek, E. F. B. Shands, and G. R. Marshall, J. Comput.-Aided Mol. Design, 3, 3 (1989). Constrained Search of Conformational Hypersurfaces.
48. SYBYL, Tripos, Inc., St. Louis, MO, 1991.
49. T. Brodmeier and E. Pretsch, J. Comput. Chem., 15, 588 (1994). Application of Genetic Algorithms in Molecular Modeling.
50. D. B. McGarrah and R. S. Judson, J. Comput. Chem., 14, 1385 (1993). An Analysis of the Genetic Algorithm Method of Molecular Conformation Determination.
51. W. P. Walters, M. T. Stahl, and D. P. Dolata, University of Arizona, Dept. of Chemistry, Tucson, AZ, 1995. Wizard III, A New 3D Model Building and Conformational Search Program.
52. W. P. Walters and D. P. Dolata, J. Mol. Graphics, 12, 130 (1994). MOUSE-III: Learning Rules of Conformational Analysis from X-Ray Data.
53. D. P. Dolata and W. P. Walters, J. Mol. Graphics. 11, 112 (1993). Short-Term Learning in Conformational Analysis.
54. D. P. Dolata and W. P. Walters, J. Mol. Graphics, 11, 106 (1993). MOUSE: A Teachable Program for Learning in Conformational Analysis.
55. P. Tuffery, C. Etchebest, S. Hazout, and R. Lavery, J. Biomol. Struct. Dynam., 8, 1267 (1991). A New Approach to the Rapid Determination of Protein Side Chain Conformations.
56. P. Tuffery, C. Etchebest, S. Hazout, and R. Lavery, J. Comput. Chem., 14, 790 (1993). A Critical Comparison of Search Algorithms Applied to the Optimization of Protein Side Chain Conformations.
57. R. Judson, Sandia National Laboratories, Livermore, CA, 1996, Report. No. SAND95-85785. Computational Evolution of a Model Polymer That Folds to a Specified Target Conformation.
58. T. Dandekar and P. Argos, Protein Eng., 5, 637 (1992). Potential of Genetic Algorithms in Protein Folding and Protein Engineering Simulations.
59. T. Dandekar and P. Argos, J. Mol. Biol., 236, 844 (1994). Folding the Main Chain of Small Proteins with the Genetic Algorithm.
60. R. Unger and J. Moult, J. Mol. Biol., 231, 75 (1993). Genetic Algorithms for Protein Folding Simulations.
61. K. F. Lau and K. A. Dill, Proc. Natl. Acad. Sci. USA, 87, 638 (1990). Theory for Protein Mutability and Biogenesis.
62. R. Unger and J. Moult, in Computer Aided Innovation of New Materials, M. Doyama, J. Kihara, M. Tanaka, and R. Yamamoto, Eds., Elsevier Science Publishers B.V., New York, 1993, pp. 1283-1286. Effects of Mutations on the Performance of Genetic Algorithms Suitable for Protein Folding Simulations.
63. S. Sun, Protein Sci., 2, 762 (1993). Reduced Representation Model of Protein Structure Prediction: Statistical Potential and Genetic Algorithms.
64. S. LeGrand and K. Merz, J. Global Opt., 3, 49 (1993). The Application of the Genetic Algorithm to the Minimization of Potential Energy Functions.
65. S. Weiner, P. Kollman, D. Nguyen, and D. Case, J. Comput. Chem., 7, 230 (1986). An All Atom Force Field for Simulations of Proteins and Nucleic Acids.
66. D. T. Jones, Protein Sci., 3, 567 (1994). De Novo Protein Design Using Pairwise Potentials and a Genetic Algorithm.
67. J. R. Gunn, A. Monge, R. A. Friesner, and C. H. Marshall, J. Phys. Chem., 98, 702 (1994). Hierarchical Algorithm for Computer Modeling of Protein Tertiary Structure: Folding of Myoglobin to 6.2 Å Resolution.
68. C. S. Ring and F. E. Cohen, Isr. J. Chem., 34, 245 (1994). Conformational Sampling of Loop Structures Using Genetic Algorithms.
69. L. D. Merkle, G. H. Gates, G. B. Lamont, and R. R. Pachter, in Proceedings of the Intel Supercomputer Users' Group 1994 Annual North American Conference, J. Wold, Ed., Intel Supercomputer Systems Division, Beaverton, OR, 1994, pp. 189-195. Application of the Parallel Fast Messy Genetic Algorithm to the Protein Folding Problem.
70. F. Herrmann and S. Suhai, J. Comput. Chem., 16, 1434 (1995). Energy Minimization of Peptide Analogues Using Genetic Algorithms. F. Herrmann and S. Suhai, in Computational Methods in Genome Research, S. Suhai, Ed., Plenum Press, New York, 1994, pp. 173-190. Genetic Algorithms in Protein Structure Prediction.
71. F. Herrmann and S. Suhai, J. Comput. Chem., 16, 1434 (1995). Energy Minimization of Peptide Analogues Using Genetic Algorithms. F. Herrmann and S. Suhai, in Computational Methods in Genome Research, S. Suhai, Ed., Plenum Press, New York, 1994, pp. 173-190. Genetic Algorithms in Protein Structure Prediction.
72. J. S. Dixon, in Trends in QSAR for Molecular Modeling, '92, Proceedings of the European Symposium on Structure-Activity Relationships, C. G. Wermuth, Ed., ESCOM, Leiden, The Netherlands, 1992, pp. 312-313. Flexible Docking of Ligands to Receptor Sites Using Genetic Algorithms.
73. I. D. Kuntz, J. M. Blaney, S. J. Oatley, R. Langridge, and T. E. Ferrin, J. Mol. Biol., 161, 269 (1982). A Geometric Approach to Macromolecule-Ligand Interactions.
74. C. M. Oshiro, I. D. Kuntz, and J. S. Dixon, J. Comput.-Aided MoI. Design, 9, 113 (1995). Flexible Ligand Docking Using a Genetic Algorithm.
75. R. S. Judson, E. P. Jaeger, and A. M. Treasurywala, J. Mol. Struct. (THEOCHEM), 308, 191 (1994). A Genetic Algorithm-Based Method for Docking Flexible Molecules.
76. R. S. Judson, Y. T. Tan, E. Mori, C. F. Melius, E. P. Jaeger, A. M. Treasurywala, and A. Mathiowetz, J. Comput. Chem., 16, 1405 (1995). Docking Flexible Molecules: A Case Study of 3 Proteins.
77. K. P. Clark and Ajay, J. Comput. Chem., 16, 1210 (1995). Flexible Ligand Docking Without Parameter Adjustment Across Four Ligand-Receptor Complexes.
78. D. K. Gehlhaar, G. M. Verkhivker, P. A. Rejto, C. J. Sherman, D. B. Fogel, L. J. Fogel, and S. T. Freer, Chem. Biol., 2, 317 (1995). Molecular Recognition of the Inhibitor AG-1343 by HIV-1 Protease: Conformationally Flexible Docking by Evolutionary Programming.
79. G. Jones, P. Willett, and R. C. Glen, J. Mol. Biol. 245, 43 (1995). Molecular Recognition of Receptor Sites Using a Genetic Algorithm with a Description of Desolvation.
80. C. B. Lucasius, M. J. J. Blommers, L. M. C. Buydens, and G. Kateman, in Handbook of Genetic Algorithms, L. Davis, Ed., Van Nostrand Reinhold, New York, 1991, pp. 251-281. A Genetic Algorithm for Conformational Analysis of DNA.
81. H. Ogata, Y. Akiyama, and M. Kanehisa, Genome Information Service, 4, 270 (1993). A Computer Modeling Method for the Three-Dimensional Structure of RNA.
82. P. Schuster, Springer Ser. Synerget., 44, 101 (1989). Optimization and Complexity in Molecular Biology and Physics.
83. M. J. J. Blommers, C. B. Lucasius, G. Kateman, and R. Kaptein, Biopolymers, 32, 45 (1992). Conformational Analysis of a Dinucleotide Photodimer with the Aid of the Genetic Algorithm.
84. J. Chang and M. Lewis, Acta Crystallogr., Sect. D, 50, 667 (1994). Using Genetic Algorithms for Solving Heavy-Atom Sites.
85. M. J. Buerger, Contemporary Crystallography, McGraw-Hill, New York, 1970.
86. A. W. R. Payne and R. C. Glen, J. Mol. Graphics, 11, 74 (1993). Molecular Recognition Using a Binary Genetic Search Algorithm.
87. D. E. Clark, G. Jones, P. Willett, P. W. Kenny, and R. C. Glen, J. Chem. Inf. Comput. Sci., 34, 197 (1994). Pharmacaphoric Pattern Matching in Files of Three-Dimensional Chemical Structures: Comparison of Conformational Searching Algorithms for Flexible Molecules.
88. J. M. Blaney and J. S. Dixon, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1994, Vol. 5, pp. 299-335. Distance Geometry in Molecular Modeling.
89. J. M. Blaney, G. M. Crippen, A. Dearing, and J. S. Dixon, Quantum Chemistry Program Exchange, Indiana University, Bloomington, IN, 1988. DGEOM: Distance Geometry.
90. P. S. Shenkin, D. L. Yarmush, R. M. Fine, H. Wang, and C. Levinthal, Biopolymers, 26, 2053 (1987). Predicting Antibody Hypervariable Loop Conformation: I. Ensembles of Random Conformations for Ringlike Structures.
91. A. C. W. May and M. S. Johnson, Protein Eng., 7, 475 (1994). Protein Structure Comparisons Using a Combination of a Genetic Algorithm, Dynamic Programming and Least-Squares Minimization.
92. M. L. Fredman, Bull. Math. Biol., 46, 553 (1984). Algorithms for Computing Evolutionary Similarity Measures with Length Independent Gap Penalties.
93. S. B. Needleman and C. Wunsch, J. Mol. Biol., 48, 444 (1970). A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins.
94. D. E. Walters and R. M. Hinds, J. Med. Chem., 37, 2527 (1994). Genetically Evolved Receptor Models: A Computational Approach to Construction of Receptor Models.
95. B. R. Brooks, R. E. Bruccoleri, B. D. Olafson, D. J. States, S. Swaminathan, and M. Karplus, J. Comput. Chem., 4, 187 (1983). CHARMM: A Program for Macromolecular Energy, Minimization, and Dynamics Calculations.
96. E. Fontain, Anal. Chim. Acta, 265, 227 (1992). The Problem of Atom-to-Atom Mapping. An Application of Genetic Algorithms.
97. E. Fontain, J. Chem. Inf. Comput. Sci., 32, 748 (1992). Application of Genetic Algorithms in the Field of Constitutional Similarity.
98. C. Jochum, J. Gasteiger, and I. Ugi, Angew. Chem. Int. Ed. Engl., 19, 495 (1980). The Principle of Minimum Chemical Distance (PMCD).
99. J. Dugundji and I. Ugi, Top. Curr. Chem., 39, 19 (1973). An Algebraic Model of Constitutional Chemistry as a Basis for Chemical Computer Programs.
100. R. D. Brown, G. Jones, P. Willett, and R. C. Glen, J. Chem. Inf. Comput. Sci., 34, 63 (1994). Matching Two-Dimensional Chemical Graphs Using Genetic Algorithms.
101. R. D. Brown, G. M. Downs, G. Jones, and P. Willett, J. Chem. Inf. Comput. Sci., 34, 47 (1994). Hyperstructure Model for Chemical Structure Handling: Techniques for Substructure Searching.
102. G. Vladutz and S. R. Gould, in The International Language of Chemistry, W. A. Warr, Ed., Springer Verlag, Berlin, 1988, pp. 371-384. Joint Compound/Reaction Storage and Retrieval and Possibilities of a Hyperstructure-Based Solution.
103. D. B. Hibbert, Chemometrics Intell. Lab. Syst., 20, 35 (1993). Generation and Display of Chemical Structures by Genetic Algorithms.
104. D. Rogers and A. J. Hopfinger, J. Chem. Inf. Comput. Sci., 34, 854 (1994). Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships.
105. J. Friedman, Laboratory of Computational Statistics, Department of Statistics, Stanford University, Report No. 102, 1990. Multivariate Adaptive Regression Splines.
106. V. Venkatasubramanian and J. M. Caruthers, Comput. Chem. Eng., 18, 833 (1994). Computer-Aided Molecular Design Using Genetic Algorithms.
107. D. Weininger, A. Weininger, and W. L. Weminger, J. Chem. Inf. Comput. Sci., 29, 97 (1989). SMILES 2: Algorithm for Generation of Unique Smiles Notation.
108. M. J. Cinkosky, J. W. Fickett, W. M. Barber, M. A. Bridgers, and C. D. Troup, Los Alamos Science, 20, 267 (1992). SIGMA: System for Integrated Genome Map Assembly.
109. G. Schneider and P. Wrede, J. Mol. Evol., 36, 586 (1993). Development of Artificial Neural Filters for Pattern Recognition in Protein Sequences.
110. G. Schneider and P. Wrede, Biophys. J., 66, 335 (1994). The Rational Design of Amino Acid Sequences by Artificial Neural Networks and Simulated Molecular Evolution: De Novo Design of an Idealized Leader Peptidase Cleavage Site.
111. G. Füllen and D. C. Youvan, Complexity International (http://www.csu.edu.au/ci/voll/ fullen/REM.html), 1, unpaged (1995). Genetic Algorithms and Recursive Ensemble Mutagenesis in Protein Engineering.
112. V. R. Vemuri and W. Cedeño, in Genetic Algorithms and Applications, L. Chambers, Ed., CRC Press, Boca Raton, Florida, 1995, Vol. 2, pp. 5-29. Multi-Niche Crowding for Multimodal Search.
113. S. W. Mahfoud, in Proceedings of Parallel Problem Solving from Nature 2, R. Männer and B. Manderick, Eds., Elsevier Science Publishers B.V., Amsterdam, 1992, pp. 27-36. Crowding and Preselection Revisited.
114. A. Ishikawa, T. Toya, Y. Totoki, and A. Konagaya, Institute for New Generation Computer Technology, Tokyo, Report No. ICOT TR-0849, 1993. Parallel Iterative Aligner with Genetic Algorithm.
115. C. B. Lucasius, A. D. Dane, and G. Kateman, Anal. Chim. Acta, 282, 647 (1993). On k-Medoid Clustering of Large Data Sets with the Aid of a Genetic Algorithm: Background, Feasibility and Comparison.
116. L. Kaufman and W. Rousseeu, Finding Groups in Data. An Introduction to Cluster Analysis, Wiley, Chichester, U.K., 1990.
117. C. B. Lucasius and G. Kateman, Trends Anal. Chem., 10, 254 (1991). Genetic Algorithms for Large Scale Optimization in Chemometrics: An Application.
118. C. B. Lucasius, A. P. d. Weijer, L. M. C. Buydens, and G. Kateman, Chemometrics Intell. Lab. Syst., 19, 337 (1993). CFIT: A Genetic Algorithm for Survival of the Fitting.
119. C. B. Lucasius, M. L. M. Beckers, and G. Kateman, Anal. Chim. Acta, 286, 135 (1994). Generic Algorithms in Wavelength Selection: a Comparative Study.
120. A. P. d. Weijer, C. B. Lucasius, L. Buydens, and G. Kateman, Chemometrics Intell. Lab. Syst., 20, 45 (1993). Using Genetic Algorithms for an Artificial Neural Network Model Inversion.
121. D. B. Hibbert, Chemometrics Intell. Lab. Syst., 19, 319 (1993). A Hybrid Genetic Algorithm for the Estimation of Kinetic Parameters.
122. R. Leardi, R. Boggia, and M. Terrile, J. Chemomet., 6, 267 (1992). Genetic Algorithms as a Strategy for Feature Selection.
123. R. Leardi, J. Chemometrics, 8, 65 (1994). Application of a Genetic Algorithm to Feature Selection Under Full Validation Conditions and to Outlier Detection.
124. I. Rossi and D. G. Truhlar, Chem. Phys. Lett., 233, 231 (1995). Parameterization of NDDO Wavefunctions Using Genetic Algorithms. An Evolutionary Approach to Parameterizing Potential Energy Surfaces and Direct Dynamics for Organic Reactions.
125. A. R. Leach, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1991, Vol. 2, pp. 1-55. A Survey of Methods for Searching the Conformational Space of Small and Medium-Sized Molecules.
126. N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller, J. Chem. Phys., 21, 1087 (1953). Equation of State Calculations by Fast Computing Machines.
127. S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Science, 220, 671 (1983). Optimization by Simulated Annealing.
128. J. A. Nelder and R. Mead, Computer J., 7, 308 (1965). A Simplex Method for Optimization.
129. C. D. Maranas and C. A. Floudas, J. Chem. Phys., 100, 1247 (1994). A Deterministic Global Optimization Approach for Molecular Structure Determination.
130. M. Saunders, J. Am. Chem. Soc., 109, 3150 (1987). Stochastic Exploration of Molecular Mechanics Energy Surfaces, Hunting for the Global Minimum.
131. D. Wienke, C. B. Lucasius, and G. Kateman, Anal. Chim. Acta, 265, 211 (1992). Multicriteria Target Vector Optimization of Analytical Procedures Using a Genetic Algorithm.
132. S. A. Allison, S. H. Northrup, and J. A. McCammon, J. Chem. Phys., 83, 2894 (1985). Extended Brownian Dynamics of Diffusion Controlled Reactions.
133. S. H. Northrup and H. P. Erickson, Proc. Natl. Acad. Sci. USA, 89, 3338 (1992). Kinetics of Protein-Protein Association Explained by Brownian Dynamics Computer Simulation.
134. D. Meyer, C. B. Naylor, I. Motoc, and G. R. Marshall, J. Comput.-Aided Mol. Design, 1, 3 (1987). Docking by Systematic Search.
135. W. C. Guida, R. S. Bohacek, and M. D. Erion, J. Comput. Chem., 13, 214 (1992). Probing the Conformational Space Available to Inhibitors in the Thermolysin Active Site Using Monte Carlo/Energy Minimization Techniques.
136. D. S. Goodsell and A. J. Olson, Proteins: Struct. Funct. Genet., 8, 195 (1990). Automated Docking of Substrates to Proteins by Simulated Annealing.
137. I. D. Kuntz, Science, 257, 1078 (1992). Structure-Based Strategies for Drug Design and Discovery.
138. E. C. Meng, B. K. Schoichet, and I. D. Kuntz, J. Comput. Chem., 13, 505 (1992). Automated Docking with Grid-Based Energy Evaluation.
139. B. K. Shoichet and I. D. Kuntz, J. Mol. Biol., 221, 327 (1991). Protein Docking and Complementarity.
140. B. K. Shoichet, R. M. Stroud, D. V. Santi, I. D. Kuntz, and K. M. Perry, Science, 259, 1445 (1993). Structure-Based Discovery of Inhibitors of Thymidylate Synthase.
141. L. Banci, S. Schroder, and P. A. Kollman, Proteins: Struct. Funct. Genet., 13, 288 (1992). Molecular Dynamics Characterization of the Active Cavity of Carboxypeptidase-A and Some of its Inhibitor Adducts.
142. B. L. Stoddard and D. E. Koshland, Proc. Natl. Acad. Sci. USA, 90, 1146 (1993). Molecular Recognition Analyzed by Docking Simulations - The Aspartate Receptor and Isocitrate Dehydrogenase from Escherichia coli.
143. C. A. Freeman, C. R. A. Catlow, J. M. Thomas, and S. Brode, Chem. Phys. Lett., 186, 137 (1991). Computing the Location and Energetics of Organic Molecules in Microporous Adsorbates and Catalysts: A Hybrid Approach Applied to Isomeric Butenes in a Model Zeolite.
144. A. R. Leach and I. D. Kuntz, J. Comput. Chem., 13, 730 (1992). Conformational Analysis of Flexible Ligands in Macromolecular Receptor Sites.
145. J. B. Moon and W. J. Howe, Tetrahedron Comput. Method, 3, 697 (1990). 3D Database Searching and De Novo Construction Methods in Molecular Design.
146. S. H. Rotstein and M. A. Murcko, J. Comput.-Aided Mol. Design, 7, 23 (1993). GEN-STAR - A Method for De Novo Drug Design.
147. S. Gallion and D. Ringe, Protein Eng., 5, 291 (1992). Molecular Modeling Studies of the Complex Between Cyclophilin and Cyclosporin-A.
148. J. M. Blaney and J. S. Dixon, Ann. Rep. Med. Chem., 26, 281 (1991). Receptor Modeling by Distance Geometry.
149. J. D. Schaffer, Ed., Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufman, San Mateo, CA, 1989.
150. L. Davis, Ed., Genetic Algorithms and Simulated Annealing, Pitman Publishing, London, 1987.
151. J. Heitkötter and D. Beasley, USENET:comp.ai.genetic, 1994. Available by anonymous FTP from rtfm.mit.edu:/pub/usenet.news.answers/ai-faq/genetic/. The Hitch-Hiker's Guide to Evolutionary Computation: A List of Frequently Asked Questions (FAQ).