Towards human-human-computer interaction for biologically-inspired problem-solving in human genetics

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Jason H. Moore and Nate Barney and Bill C. White",
  title =        "Towards human-human-computer interaction for
                 biologically-inspired problem-solving in human
  booktitle =    "GECCO '07: Proceedings of the 9th annual conference on
                 Genetic and evolutionary computation",
  year =         "2007",
  editor =       "Dirk Thierens and Hans-Georg Beyer and 
                 Josh Bongard and Jurgen Branke and John Andrew Clark and 
                 Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and 
                 Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and 
                 Julian F. Miller and Jason Moore and Frank Neumann and 
                 Martin Pelikan and Riccardo Poli and Kumara Sastry and 
                 Kenneth Owen Stanley and Thomas Stutzle and 
                 Richard A Watson and Ingo Wegener",
  volume =       "1",
  isbn13 =       "978-1-59593-697-4",
  pages =        "432--433",
  address =      "London",
  URL =          "",
  DOI =          "doi:10.1145/1276958.1277052",
  publisher =    "ACM Press",
  publisher_address = "New York, NY, USA",
  month =        "7-11 " # jul,
  organisation = "ACM SIGEVO (formerly ISGEC)",
  keywords =     "genetic algorithms, genetic programming, Biological
                 Applications: Poster, genetic analysis, genetic
                 epidemiology, human factors, Open Source Software,
                 symbolic discriminant analysis, symbolic regression",
  abstract =     "Genetic programming (GP) shows great promise for
                 solving complex problems in human genetics.
                 Unfortunately, many of these methods are not accessible
                 to biologists. This is partly due to the complexity of
                 the algorithms that limit their ready adoption and
                 integration into an analysis or modelling paradigm that
                 might otherwise only use univariate statistical
                 methods. This is also partly due to the lack of
                 user-friendly, open-source, platform independent, and
                 freely-available software packages that are designed to
                 be used by biologists for routine analysis. It is our
                 objective to develop, distribute and support a
                 comprehensive software package that puts powerful GP
                 methods for genetic analysis in the hands of
                 geneticists. It is our working hypothesis that the most
                 effective use of such a software package would result
                 from interactive analysis by both a biologist and a
                 computer scientist (i.e. human-human-computer
                 interaction). We summarise briefly here the design and
                 implementation of an open-source software package
                 called Symbolic Modeler (SyMod) that seeks to
                 facilitate geneticist-bioinformaticist-computer
                 interactions for problem solving in human genetics.
                 More information can be found at or
  notes =        "GECCO-2007 A joint meeting of the sixteenth
                 international conference on genetic algorithms
                 (ICGA-2007) and the twelfth annual genetic programming
                 conference (GP-2007).

                 ACM Order Number 910071",

Genetic Programming entries for Jason H Moore Nate Barney Bill C White