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2018 | OriginalPaper | Chapter

Evolving Better RNAfold Structure Prediction

Authors : William B. Langdon, Justyna Petke, Ronny Lorenz

Published in: Genetic Programming

Publisher: Springer International Publishing

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Abstract

Grow and graft genetic programming (GGGP) evolves more than 50000 parameters in a state-of-the-art C program to make functional source code changes which give more accurate predictions of how RNA molecules fold up. Genetic improvement updates 29% of the dynamic programming free energy model parameters. In most cases (50.3%) GI gives better results on 4655 known secondary structures from RNA_STRAND (29.0% are worse and 20.7% are unchanged). Indeed it also does better than parameters recommended by Andronescu, M., et al.: Bioinformatics 23(13) (2007) i19–i28.

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The ViennaRNA package must first be configured with ./configure –enable-sse. https://www.tbi.univie.ac.at/RNA/documentation.html.

Tsunoda, M., et al.: Structural basis for recognition of cognate tRNA by tyrosyl-tRNA synthetase from 3 kingdoms. Nucleic Acids Res. 35(13), 4289–4300 (2007). https://doi.org/10.1093/nar/gkm417 CrossRef

Crick, F.: Central dogma of molecular biology. Nature 227, 561–563 (1970). https://doi.org/10.1038/227561a0 CrossRef

Andronescu, M., et al.: RNA STRAND: The RNA secondary structure and statistical analysis database. BMC Bioinformatics 9(1), 340 (2008). https://doi.org/10.1186/1471-2105-9-340 MathSciNetCrossRef

Reeder, J., et al.: pknotsRG: RNA pseudoknot folding including near-optimal structures and sliding windows. Nucleic Acids Res. 35(Suppl 2), W320–W324 (2007). https://doi.org/10.1093/nar/gkm258 CrossRef

Langdon, W.B., Harman, M.: Grow and graft a better CUDA pknotsRG for RNA Pseudoknot free energy calculation. In: GI 2015 Workshop, pp. 805–810 (2015). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/langdon_2015_gi_pknots.html

Lorenz, R., et al.: ViennaRNA package 2.0. Algorithms Mol. Biol. 6(1), 26 (2011). https://doi.org/10.1186/1748-7188-6-26 CrossRef

Lee, J., et al.: RNA design rules from a massive open laboratory. PNAS 111(6), 2122–2127 (2013). https://doi.org/10.1073/pnas.1313039111 CrossRef

Harman, M., Jia, Y., Langdon, W.B.: Babel Pidgin: SBSE can grow and graft entirely new functionality into a real world system. In: Le Goues, C., Yoo, S. (eds.) SSBSE 2014. LNCS, vol. 8636, pp. 247–252. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-09940-8_20

Jia, Y., Harman, M., Langdon, W.B., Marginean, A.: Grow and serve: growing Django citation services using SBSE. In: Barros, M., Labiche, Y. (eds.) SSBSE 2015. LNCS, vol. 9275, pp. 269–275. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22183-0_22 CrossRef

10.

Kocsis, Z.A., Swan, J.: Genetic programming + proof search = automatic improvement. J. Autom. Reasoning 60(2), 157–176 (2018). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/PolyfinicJAR.html MathSciNetCrossRefMATH

11.

Langdon, W.B., Lam, B.Y.H., Petke, J., Harman, M.: Improving CUDA DNA analysis software with genetic programming. In: GECCO, pp. 1063–1070 (2015). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Langdon_2015_GECCO.html

12.

Langdon, W.B.: Genetic improvement of software for multiple objectives. In: Barros, M., Labiche, Y. (eds.) SSBSE 2015. LNCS, vol. 9275, pp. 12–28. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22183-0_2 CrossRef

13.

Langdon, W.B., Lam, B.Y.H., Modat, M., Petke, J., Harman, M.: Genetic improvement of GPU software. GP & EM 18(1), 5–44 (2017). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Langdon_2016_GPEM.html

14.

Langdon, W.B: Genetically improved software. In: Gandomi, A.H., et al. (Eds.): Handbook of Genetic Programming Applications, pp. 181–220. Springer, Cham (2015). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/langdon_2015_hbgpa.html

15.

Petke, J., Haraldsson, S.O., Harman, M., Langdon, W.B., White, D.R., Woodward, J.R.: Genetic improvement of software: a comprehensive survey. IEEE Transactions on Evolutionary Computation (In press). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Petke_gisurvey.html

16.

Langdon, W.B., Harman, M.: Optimising existing software with genetic programming. IEEE Trans. Evol. Comput. 19(1), 118–135 (2015). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Langdon_2013_ieeeTEC.html CrossRef

17.

Bruce, B.R., Petke, J., Harman, M.: Reducing energy consumption using genetic improvement. In: GECCO, pp. 1327–1334. ACM (2015)

18.

Wu, F., Weimer, W., Harman, M., Jia, Y., Krinke, J.: Deep parameter optimisation. In: Silva, S., et al., (Eds.) GECCO, pp. 1375–1382 (2015). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Wu_2015_GECCO.html

19.

Marginean, A., Barr, E.T., Harman, M., Jia, Y.: Automated transplantation of call graph and layout features into kate. In: Barros, M., Labiche, Y. (eds.) SSBSE 2015. LNCS, vol. 9275, pp. 262–268. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22183-0_21 CrossRef

20.

Le Goues, C., Nguyen, T., Forrest, S., Weimer, W.: GenProg: a generic method for automatic software repair. IEEE Trans. Softw. Eng. 38(1), 54–72 (2012). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/DBLP_journals_tse_GouesNFW12.html CrossRef

21.

Langdon, W.B., Lorenz, R.: Improving SSE parallel code with grow and graft genetic programming. In: Petke, J., et al. (Eds.) GI-2017, pp. 1537–1538. ACM (2017). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Langdon_2017_GI.html

22.

Koza, J.R.: Genetic Programming. MIT press, Cambridge, MA (1992). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/koza_book.html MATH

23.

Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D.: Genetic Programming - An Introduction. Morgan Kaufmann, San Francisco (1998). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/banzhaf_1997_book.html CrossRefMATH

24.

Poli, R., Langdon, W.B., McPhee, N.F.: A field guide to genetic programming. Lulu Enterprises, UK (2008). http://www.gp-field-guide.org.uk

25.

Das, R.: Personal Communication (2017)

26.

Langdon, W.B.: Evolving better RNAfold C source code. Technical Report RN/17/08, University College, London, (2017). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/langdon_RN1708.html

27.

MacKerell Jr., A.D., Banavali, N., Foloppe, N.: Development and current status of the CHARMM force field for nucleic acids. Biopolymers 56(4), 257–265 (2000). https://doi.org/10.1002/1097-0282(2000)56:4%3c257::AID-BIP10029%3e3.0.CO;2-W CrossRef

28.

Zuber, J., et al.: A sensitivity analysis of RNA folding nearest neighbor parameters identifies a subset of free energy parameters with the greatest impact on RNA secondary structure prediction. Nucleic Acids Res. 45(10), 6168–6176 (2017). https://doi.org/10.1093/nar/gkx170 CrossRef

29.

Angeline, P.J.: Multiple interacting programs: a representation for evolving complex behaviors. Cybern. Syst. 29(8), 779–803 (1998). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/angeline_1998_mips3.html CrossRefMATH

30.

Langdon, W.B.: Genetic Programming and Data Structures. Kluwer, Norwell (1998). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/langdon_book.html CrossRefMATH

31.

Langdon, W.B., Lam, B.Y.H.: Genetically improved BarraCUDA. BioData Min., 20(28) (2017). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Langdon_2017_BDM.html

32.

Weimer, W., Nguyen, T., Le Goues, C., Forrest, S.: Automatically finding patches using genetic programming. In: ICSE, pp. 364–374 (2009). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Weimer_2009_ICES.html

33.

Andronescu, M., et al.: Efficient parameter estimation for RNA secondary structure prediction. Bioinformatics 23(13), i19–i28 (2007). https://doi.org/10.1093/bioinformatics/btm223 CrossRef

34.

Schmidt, M., Lipson, H.: Distilling free-form natural laws from experimental data. Science 324(5923), 81–85 (2009). http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Science09_Schmidt.html CrossRef

Title: Evolving Better RNAfold Structure Prediction
Authors: William B. Langdon
Justyna Petke
Ronny Lorenz
Publisher: Springer International Publishing
Book: Genetic Programming
Print ISBN: 978-3-319-77552-4

Electronic ISBN: 978-3-319-77553-1

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-77553-1_14

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