Performance of genetic programming optimised Bowtie2 on genome comparison and analytic testing (GCAT) benchmarks

BioData Mining

Volumn 8, Issue 1, 2015, Pages

  Langdon, W B ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Double ended DNA sequence; High throughput Solexa 454 nextgen NGS sequence query; Homo sapiens genome reference consortium HG19; Rapid fuzzy string matching

Indexed keywords

ARTICLE; AUTOMATION; BENCHMARKING; BIOINFORMATICS; BOWTIE2 SOFTWARE; CONTROLLED STUDY; DNA SEQUENCE; FUZZY SYSTEM; GENETIC ENGINEERING; GENOME ANALYSIS; GENOME SIZE; GENOMICS; HUMAN; MEASUREMENT ACCURACY; NEXT GENERATION SEQUENCING; PRIORITY JOURNAL; SEQUENCE ALIGNMENT; SOFTWARE; THOUSAND GENOME PROJECT;

EID: 84988579306     PISSN: None     EISSN: 17560381     Source Type: Journal    
DOI: 10.1186/s13040-014-0034-0     Document Type: Article

References (22)

1. Shen L, Shao N, Liu X, Nestler E: ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases. BMC Genomics 2014, 15:284. Software. http://dx.doi.org/doi:10.1186/1471-2164-15-284
2. Schuster SC: Next-generation sequencing transforms today's biology. Nat Methods 2008, 5(1):16-18. http://dx.doi.org/10.1038/nmeth1156
3. Durbin RM: Amap of human genome variation from population-scale sequencing. Nature 2010, 467(7319):1061-1073. http://dx.doi.org/10.1038/nature09534
4. Langdon WB: Mycoplasma contamination in the 1000 genomes project. BioData Mining 2014, 7(3). Highly accessed. http://dx.doi.org/10.1186/1756-0381-7-3
5. Shapiro JA, von Sternberg R: Why repetitive DNA is essential to genome function. Biol Rev 2005, 80:1-24. http://dx.doi.org/10.1017/S1464793104006657
6. Fullwood MJ, Wei C-L, Liu ET, Ruan Y: Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses. Genome Res 2009, 19(4):521-532. http://dx.doi.org/10.1101/gr.074906.107
7. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST a new generation of protein database search programs. Nucleic Acids Res 1997, 25(17):3389-3402. http://dx.doi.org/10. 1093/nar/25.17.3389
8. Langmead B, Trapnell C, Pop M, Salzberg S: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009, 10(3):R25. http://dx.doi.org/10.1186/gb-2009-10-3-r25
9. Langmead B, Salzberg SL: Fast gapped-read alignment with Bowtie 2. Nat Methods 2012, 9(4):357-359. http://dx.doi.org/10.1038/nmeth.1923
10. Li H, Durbin R: Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 2010, 26(5):589-595. http://dx.doi.org/10.1093/bioinformatics/btp698
11. Koza JR: Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA, USA: MIT Press; 1992. http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/koza-book.html
12. Poli R, Langdon WB, McPhee NF: A field guide to genetic programming. Published via http://lulu.com and freely available at http://www.gp-field-guide.org.uk, 2008 (With contributions by J. R. Koza). http://www.cs.bham.ac.uk/~ wbl/biblio/gp-html/poli08-fieldguide.html
13. Holland JH: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence: MIT Press; 1992. First Published by University of Michigan Press 1975.
14. Goldberg DE: Genetic Algorithms in Search Optimization and Machine Learning: Addison-Wesley; 1989.
15. Bäck T: Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic, Algorithms. New York: Oxford University Press; 1996.
16. Darwin C: The Origin of Species. 1985edition: John Murray, penguin classics; 1859.
17. Harman M: Software engineeringmeets evolutionary computation. Computer 2011, 44(10):31-39. Cover feature. http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Harman-2011-ieeeC.html
18. Langdon WB, Harman M: Optimising existing software with genetic programming. IEEE Trans Evol Comput. Accepted. http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Langdon-2013-ieeeTEC.html
19. Langdon WB: Which is faster: Bowtie2GP > Bowtie > Bowtie2 > BWA. In GECCO 2013 Late breaking abstracts workshop. Edited by Francisco Luna. Amsterdam, The NetherlandsL: ACM; 2013:1741-1742. http://www.cs.bham.ac. uk/~wbl/biblio/gp-html/Langdon-2013-GECCOlb.html
20. Zook JM, Chapman B, Wang J, Mittelman D, Hofmann O, Hide W, Salit M: Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls. Nat Biotechnol 2014, 32(3):246-251. http://dx.doi.org/10.1038/nbt.2835
21. Harman M, Langdon WB, Jia Y, White DR, Arcuri A, Clark JA: The GISMOE challenge: Constructing the Pareto program surface using genetic programming to find better programs. In The 27th IEEE/ACM International Conference on Automated Software Engineering (ASE 12). Essen, Germany: ACM; September 3-7 2012:1-14. http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/Harman-2012-ASE.html
22. Petke J, Harman M, Langdon WB, Weimer W: Using genetic improvement and code transplants to specialise a C++ program to a problem class. In 17th European Conference on Genetic Programming. Volume 8599 of LNCS. Edited by Miguel Nicolau, Krzysztof Krawiec, Malcolm I. Heywood, Mauro Castelli, Pablo Garcia-Sanchez, Juan J. Merelo, Victor M. Rivas Santos, Kevin Sim. Granada, Spain: Springer; 23-25 April 2014:137-149. http://www.cs.bham. ac.uk/~wbl/biblio/gp-html/Petke-2014-EuroGP.html