Solving complex problems in human genetics using genetic programming: the importance of theorist-practitioner-computer interaction. 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 modeling 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 interactions). We present 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. We present and discuss the results of an application of SyMod to real data and discuss the challenges associated with delivering a user-friendly GP-based software package to the genetics community.
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References in zbMATH (referenced in 1 article , 1 standard article )
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- Moore, Jason H.; Barney, Nate; White, Bill C.: Solving complex problems in human genetics using genetic programming: the importance of theorist-practitioner-computer interaction (2008)