- author = "William B. Langdon and Karina Zile",
- title = "Genetic Improvement of Computational Biology Software",
- booktitle = "Evolutionary Computation in Computational Biology",
- year = "2017",
- editor = "Jose Santos and Julia Handl and Amarda Shehu and Mostafa Ellabaan",
- pages = "1657--1660",
- address = "Berlin",
- month = "15-19 " # jul,
- keywords = "genetic algorithms, genetic programming, genetic improvement, GGGP, search based software engineering, SBSE, software engineering, bioinformatics, next generation sequencing, NGS, DNA sequences, microarray, genechip, NCBI GEO, DNA sequences, GGGP, GI, GP, NGS, big data cleanup, molecular biology, data cleansing, in silico contamination, identification and correction of mislabelled genes, big data cleanup, hitch-hiking genes, 1k~geneomes, 1KGP, identification and correction of mislabelled genes",
- isbn13 = "978-1-4503-4939-0",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/langdon_2017_ECCSB.pdf",
-
URL = "
http://doi.acm.org/10.1145/3067695.3082540",
-
DOI = "
doi:10.1145/3067695.3082540",
- acmid = "3082540",
- size = "4 pages",
- abstract = "There is a cultural divide between computer scientists and biologists that needs to be addressed. The two disciplines used to be quite unrelated but many new research areas have arisen from their synergy. We selectively review two multi-disciplinary problems: dealing with contamination in sequencing data repositories and improving software using biology inspired evolutionary computing. Through several examples, we show that ideas from biology may result in optimised code and provide surprising improvements that overcome challenges in speed and quality trade-offs. On the other hand, development of computational methods is essential for maintaining contamination free databases. Computer scientists and biologists must always be sceptical of each others data, just as they would be of their own.",
-
notes = "slides:
http://www.cs.ucl.ac.uk/staff/W.Langdon/gecco2017/langdon_2017_eccsb_slides.pdf
http://eccsb2017.irlab.org/ Also known as \cite{Langdon:2017:GECCOa} \cite{Langdon:2017:GIC:3067695.3082540} GECCO-2017 A Recombination of the 26th International Conference on Genetic Algorithms (ICGA-2017) and the 22nd Annual Genetic Programming Conference (GP-2017)",
