Data mining the yeast genome in a lazy functional language

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dc.contributor.author Clare, Amanda
dc.contributor.author King, Ross Donald
dc.date.accessioned 2006-04-24T15:31:55Z
dc.date.available 2006-04-24T15:31:55Z
dc.date.issued 2003
dc.identifier.citation Clare , A & King , R D 2003 , ' Data mining the yeast genome in a lazy functional language ' . en
dc.identifier.other PURE: 68087
dc.identifier.other dspace: 2160/130
dc.identifier.uri http://hdl.handle.net/2160/130
dc.description Clare, A. and King R.D. (2003) Data mining the yeast genome in a lazy functional language. In Practical Aspects of Declarative Languages (PADL'03) (won Best/Most Practical Paper award). en
dc.description.abstract Critics of lazy functional languages contend that the languages are only suitable for toy problems and are not used for real systems. We present an application (PolyFARM) for distributed data mining in relational bioinformatics data, written in the lazy functional language Haskell. We describe the problem we wished to solve, the reasons we chose Haskell and relate our experiences. Laziness did cause many problems in controlling heap space usage, but these were solved by a variety of methods. The many advantages of writing software in Haskell outweighed these problems. These included clear expression of algorithms, good support for data structures, abstraction, modularity and generalisation leading to fast prototyping and code reuse, parsing tools, profiling tools, language features such as strong typing and referential transparency, and the support of an enthusiastic Haskell community. PolyFARM is currently in use mining data from the Saccharomyces cerevisiae genome and is freely available for non-commercial use at http://www.aber.ac.uk/compsci/Research/bio/dss/polyfarm/. en
dc.language.iso eng
dc.title Data mining the yeast genome in a lazy functional language en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Bioinformatics and Computational Biology Group en
dc.description.status Non peer reviewed en


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