Abstract
In this work, we consider probabilistic models that can infer biological information solely from biological sequences such as DNA. Traditionally, computational models for biological sequence analysis have been implemented in a wide variety of procedural and object oriented programming languages [1]. Models implemented using stochastic logic programming (SLP [2,3,4]) instead, may draw upon the benefits of increased expressive power, conciseness and compositionality. It does, however, pose a big challenge to design efficient SLP models.
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Lassen, O.T. (2008). Biosequence Analysis in PRISM. In: Garcia de la Banda, M., Pontelli, E. (eds) Logic Programming. ICLP 2008. Lecture Notes in Computer Science, vol 5366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89982-2_84
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DOI: https://doi.org/10.1007/978-3-540-89982-2_84
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