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An Open-Source Sandbox for Increasing the Accessibility of Functional Programming to the Bioinformatics and Scientific Communities

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7 Author(s)
Matthew Fenwick ; Dept. of Microbial, Univ. of Connecticut Health Center, Farmington, CT, USA ; Colbert Sesanker ; Martin R. Schiller ; Heidi JC Ellis
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Scientists are continually faced with the need to express complex mathematical notions in code. The renaissance of functional languages such as LISP and Haskell is often credited to their ability to implement complex data operations and mathematical constructs in an expressive and natural idiom. The slow adoption of functional computing in the scientific community does not, however, reflect the congeniality of these fields. Unfortunately, the learning curve for adoption of functional programming techniques is steeper than that for more traditional languages in the scientific community, such as Python and Java, and this is partially due to the relative sparseness of available learning resources. To fill this gap, we demonstrate and provide applied, scientifically substantial examples of functional programming, We present a multi-language source-code repository for software integration and algorithm development, which generally focuses on the fields of machine learning, data processing, bioinformatics. We encourage scientists who are interested in learning the basics of functional programming to adopt, reuse, and learn from these examples. The source code is available at: (see also

Published in:

Information Technology: New Generations (ITNG), 2012 Ninth International Conference on

Date of Conference:

16-18 April 2012