Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
This paper describes the application of our distributed computing framework for crystal structure prediction, Modified Genetic Algorithms for Crystal and Cluster Prediction (MGAC), to predict the crystal structure of the two known polymorphs of bicalutamide. The paper describes our success in findin...
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| Formato: | Acta de conferencia Capítulo de libro |
| Lenguaje: | Inglés |
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2009
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| LEADER | 12013caa a22011057a 4500 | ||
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| 008 | 190411s2009 xx ||||fo|||| 00| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-70350391694 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 100 | 1 | |a Ferraro, Marta Beatriz | |
| 245 | 1 | 0 | |a Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs |
| 260 | |c 2009 | ||
| 270 | 1 | 0 | |m Facelli, J. C.; Center for High Performance Computing, University of Utah, 155 South 1452 East Room 405, Salt Lake City, UT 84112-0190, United States; email: julio.facelli@utah.edu |
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| 506 | |2 openaire |e Política editorial | ||
| 520 | 3 | |a This paper describes the application of our distributed computing framework for crystal structure prediction, Modified Genetic Algorithms for Crystal and Cluster Prediction (MGAC), to predict the crystal structure of the two known polymorphs of bicalutamide. The paper describes our success in finding the lower energy polymorph and the difficulties encountered in finding the second one. The results show that genetic algorithms are very effective in finding low energy crystal conformations, but unfortunately many of them are not plausible due to spurious effects introduced by the energy potential function used in the selection process. We propose to solve this by using a multi objective optimization GA approach, adding the unit cell volume as a second optimization target. © 2009 Springer Berlin Heidelberg. |l eng | |
| 593 | |a Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pab. I (1428), Buenos Aires, Argentina | ||
| 593 | |a Center for High Performance Computing, University of Utah, 155 South 1452 East Room 405, Salt Lake City, UT 84112-0190, United States | ||
| 593 | |a Department of Biomedical Informatics, University of Utah, 155 South 1452 East Room 405, Salt Lake City, UT 84112-0190, United States | ||
| 690 | 1 | 0 | |a CRYSTAL STRUCTURE PREDICTION |
| 690 | 1 | 0 | |a DRUG POLYMORPHISM |
| 690 | 1 | 0 | |a PARALLEL GENETIC ALGORITHMS |
| 690 | 1 | 0 | |a BICALUTAMIDE |
| 690 | 1 | 0 | |a CLUSTER PREDICTION |
| 690 | 1 | 0 | |a CRYSTAL CONFORMATION |
| 690 | 1 | 0 | |a CRYSTAL STRUCTURE PREDICTION |
| 690 | 1 | 0 | |a DISTRIBUTED COMPUTING |
| 690 | 1 | 0 | |a DRUG POLYMORPHISM |
| 690 | 1 | 0 | |a ENERGY POTENTIAL |
| 690 | 1 | 0 | |a LOW ENERGIES |
| 690 | 1 | 0 | |a LOWER ENERGIES |
| 690 | 1 | 0 | |a MODIFIED GENETIC ALGORITHMS |
| 690 | 1 | 0 | |a PARALLEL GENETIC ALGORITHMS |
| 690 | 1 | 0 | |a SECOND OPTIMIZATION |
| 690 | 1 | 0 | |a SELECTION PROCESS |
| 690 | 1 | 0 | |a SPURIOUS EFFECTS |
| 690 | 1 | 0 | |a UNIT-CELL VOLUME |
| 690 | 1 | 0 | |a CELL MEMBRANES |
| 690 | 1 | 0 | |a CLUSTERING ALGORITHMS |
| 690 | 1 | 0 | |a COMPUTER SCIENCE |
| 690 | 1 | 0 | |a GENETIC ALGORITHMS |
| 690 | 1 | 0 | |a INTELLIGENT COMPUTING |
| 690 | 1 | 0 | |a PARALLEL ALGORITHMS |
| 690 | 1 | 0 | |a POLYMORPHISM |
| 690 | 1 | 0 | |a CRYSTAL STRUCTURE |
| 700 | 1 | |a Orendt, A.M. | |
| 700 | 1 | |a Facelli, J.C. | |
| 711 | 2 | |c Ulsan |d 16 September 2009 through 19 September 2009 |g Código de la conferencia: 77838 | |
| 773 | 0 | |d 2009 |g v. 5754 LNCS |h pp. 120-129 |p Lect. Notes Comput. Sci. |n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |x 03029743 |w (AR-BaUEN)CENRE-983 |z 3642040691 |z 9783642040696 |t 5th International Conference on Intelligent Computing, ICIC 2009 | |
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