Data mining the yeast genome in a lazy functional language. 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/.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Srinivasan, Ashwin; Faruquie, Tanveer A.; Joshi, Sachindra: Data and task parallelism in ILP using mapreduce (2012)
- Fonseca, Nuno A.; Srinivasan, Ashwin; Silva, Fernando; Camacho, Rui: Parallel ILP for distributed-memory architectures (2008)
- Clare, Amanda; King, Ross D.: Data mining the yeast genome in a lazy functional language (2002)