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Experience report: Haskell in computational biology

Published:09 September 2012Publication History
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Abstract

Haskell gives computational biologists the flexibility and rapid prototyping of a scripting language, plus the performance of native code. In our experience, higher-order functions, lazy evaluation, and monads really worked, but profiling and debugging presented obstacles. Also, Haskell libraries vary greatly: memoization combinators and parallel-evaluation strategies helped us a lot, but other, nameless libraries mostly got in our way. Despite the obstacles and the uncertain quality of some libraries, Haskell's ecosystem made it easy for us to develop new algorithms in computational biology.

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  1. Experience report: Haskell in computational biology

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            cover image ACM SIGPLAN Notices
            ACM SIGPLAN Notices  Volume 47, Issue 9
            ICFP '12
            September 2012
            368 pages
            ISSN:0362-1340
            EISSN:1558-1160
            DOI:10.1145/2398856
            Issue’s Table of Contents
            • cover image ACM Conferences
              ICFP '12: Proceedings of the 17th ACM SIGPLAN international conference on Functional programming
              September 2012
              392 pages
              ISBN:9781450310543
              DOI:10.1145/2364527

            Copyright © 2012 ACM

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            Association for Computing Machinery

            New York, NY, United States

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            • Published: 9 September 2012

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