Using operator equalisation for prediction of drug toxicity with genetic programming

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5816 LNAI, Issue , 2009, Pages 65-76

  Vanneschi, Leonardo ^a   Silva, Sara ^b  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b UNIVERSITY OF COIMBRA   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

CODE SIZE; COMPLEX PROBLEMS; CONTROL METHODS; DRUG DESIGN; EQUALISATION; EVOLUTIONARY PROCESS; GENERAL SOLUTIONS; MOLECULAR COMPOUNDS; OVERFITTING; POTENTIAL DRUG;

ARTIFICIAL INTELLIGENCE; GENETIC ALGORITHMS; GENETIC ENGINEERING; OPTICAL COMMUNICATION; TOXICITY;

GENETIC PROGRAMMING;

EID: 71049115621     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04686-5_6     Document Type: Conference Paper

References (30)

1. Archetti, F., Lanzeni, S., Messina, E., Vanneschi, L.: Genetic programming and other machine learning approaches to predict median oral lethal dose (LD50) and plasma protein binding levels (%PPB) of drugs. In: Marchiori, E., Moore, J.H., Rajapakse, J.C. (eds.) Evo- BIO 2007. LNCS, vol.4447, pp. 11-23. Springer, Heidelberg (2007)
2. Archetti, F.,Messina, E., Lanzeni, S.,Vanneschi, L.: Genetic programming for computational pharmacokinetics in drug discovery and development. Genetic Programming and Evolvable Machines 8(4), 17-26 (2007)
3. Dignum, S., Poli, R.: Generalisation of the limiting distribution of program sizes in treebased genetic programming and analysis of its effects on bloat. In: Thierens, D., et al. (eds.) GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation, vol.2, pp. 1588-1595. ACM Press, New York (2007)
4. Dignum, S., Poli, R.: Crossover, sampling, bloat and the harmful effects of size limits. In: O'Neill,M., Vanneschi, L., Gustafson, S., Esparcia Alćazar, A.I., De Falco, I., Della Cioppa, A., Tarantino, E. (eds.) EuroGP 2008. LNCS, vol.4971, pp. 158-169. Springer, Heidelberg (2008)
5. Dignum, S., Poli, R.: Operator equalisation and bloat free GP. In: O'Neill, M., Vanneschi, L., Gustafson, S., Esparcia Alćazar, A.I., De Falco, I., Della Cioppa, A., Tarantino, E. (eds.) EuroGP 2008. LNCS, vol.4971, pp. 110-121. Springer, Heidelberg (2008)
6. Yoshida, F., Topliss, J.G.: QSAR model for drug human oral bioavailability. Journal of Medicinal Chemistry 43, 2575-2585 (2000)
7. Fernandez, F., Tomassini, M., Vanneschi, L.: An empirical study of multipopulation genetic programming. Genetic Programming and Evolvable Machines 4(1), 21-51 (2003) (Pubitemid 36107382)
8. Colmenarejo, G., Alvarez-Pedraglio, A., Lavandera, J.L.: Chemoinformatic models to predict binding affinities to human serum albumin. Journal of Medicinal Chemistry 44, 4370-4378 (2001)
9. Van de Waterbeemd, H., Rose, S.: In:Wermuth, L.G. (ed.) The Practice of Medicinal Chemistry, 2nd edn., pp. 1367-1385. Academic Press, London (2003)
10. Kola, I., Landis, J.: Can the pharmaceutical industry reduce attrition rates? Nature Reviews Dug Discovery 3, 711-716 (2004)
11. Igel, C., Chellapilla, K.: Investigating the influence of depth and degree of genotypic change on fitness in genetic programming. In: Banzhaf, W., et al. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference, vol.2, pp. 1061-1068. Morgan Kaufmann, San Francisco (1999)
12. Feng, J., Lurati, L., Ouyang, H., Robinson, T., Wang, Y., Yuan, S., Young, S.S.: Predictive toxicology: benchmarking molecular descriptors and statistical methods. Journal of Chemical Information Computer Science 43, 1463-1470 (2003)
13. Luke, S.: Modification point depth and genome growth in genetic programming. Evolutionary Computation 11(1), 67-106 (2003)
14. Luke, S., Panait, L.: Lexicographic parsimony pressure. In: Langdon, W.B., et al. (eds.) GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 829-836. Morgan Kaufmann Publishers, San Francisco (2002)
15. Poli, R., Langdon, W.B., Dignum, S.: On the limiting distribution of program sizes in treebased genetic programming. In: Ebner, M., et al. (eds.) Proceedings of the 10th European Conference on Genetic Programming, Valencia, Spain, April 11 - 13, pp. 193-204. Springer, Heidelberg (2007)
16. Poli, R., McPhee, N.F., Vanneschi, L.: The impact of population size on code growth in GP: analysis and empirical validation. In: Keijzer, M., et al. (eds.) GECCO 2008: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pp. 1275-1282. ACM, New York (2008)
17. Poli, R., Langdon, W.B., McPhee, N.F.: A field guide to genetic programming (2008) (Published), http://lulu.com, http://www.gp-field-guide.org. uk, (With contributions by J. R. Koza)
18. Todeschini, R., Consonni, V.: Handbook of Molecular Descriptors. Wiley-VCH, Weinheim (2000)
19. Rissanen, J.: Modeling by shortest data description. Automatica 14, 465-471 (1978)
20. David, S.,Wishart, Knox, C., Guo, A.C., Shrivastava, S., Hassanali, M., Stothard, P., Chang, Z.,Woolsey, J.: DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Research, 34 (2006), doi:10.1093/nar/gkj067
21. Silva, S.: GPLAB - a genetic programming toolbox for MATLAB, version 3.0 (2009) http://gplab.sourceforge.net
22. Silva, S., Almeida, J.: Dynamic maximum tree depth. In: Cant́u-Paz, E., et al. (eds.) Genetic and Evolutionary Computation - GECCO-2003, pp. 1776-1787. Springer, Heidelberg (2003)
23. Silva, S., Costa, E.: Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories. Genetic Programming and Evolvable Machines 10(2), 141-179 (2009) (Published Online January 13, 2009)
24. Silva, S., Dignum, S.: Extending operator equalisation: Fitness based self adaptive length distribution for bloat free GP. In: Vanneschi, L., et al. (eds.) Proceedings of the 12th European Conference on Genetic Programming, EuroGP2009, pp. 159-170. Springer, Heidelberg (2009)
25. Silva, S., Vanneschi, L.: Operator Equalisation, Bloat and Overfitting - A Study on Human Oral Bioavailability Prediction. In: Rothlauf, F., et al. (eds.) Proceedings of GECCO-2009, ACM Press, New York (to appear, 2009)
26. Kennedy, T.: Managing the drug discovery/development interface. Drug Discovery Today 2, 436-444 (1997)
27. Martin, T.M., Young, D.M.: Prediction of the Acute Toxicity (96-h LC50) of Organic Compounds to the Fathead Minnow (Pimephales promelas) Using a Group Contribution Method. Chemical Research in Toxicology 14(10), 1378-1385 (2001)
28. Tetko, I.V., Gasteiger, J., Todeschini, R., Mauri, A., Livingstone, D., Ertl, P., Palyulin, V.A., Radchenko, E.V., Zefirov, N.S., Makarenko, A.S., Tanchuk, V.Y., Prokopenko, V.V.: Virtual computational chemistry laboratory - design and description. Journal of Computer Aided Molecular Design 19, 453-463 (2005)
29. Vanneschi, L., Tomassini, M., Collard, P., Clergue, M.: Fitness distance correlation in structural mutation genetic programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol.2610, pp. 455-464. Springer, Heidelberg (2003)
30. Langdon, W.B., Barrett, S.J.: Genetic Programming in data mining for drug discovery. In: Evolutionary computing in data mining, pp. 211-235 (2004)