We present L-SME, a system to efficiently identify loosely structured motifs in genome-wide applications. L-SME is innovative in three aspects. Firstly, it handles wider classes of motifs than earlier motif discovery systems, by supporting boxes swaps and skips in the motifs structure as well as various kinds of similarity functions. Secondly, in addition to the standard exact search, it supports search via randomization in which guarantees on the quality of the results can be given a-priori based on user-definable resource (time and space) constraints. Finally, L-SME comes equipped with an intuitive graphical interface through which the structure for the motifs of interest can be defined, the discovery method can be selected, and results can be visualized. The tool is flexible and scalable, by allowing genome-wide searches for very complex motifs and is freely accessible at http://siloe.deis.unical.it/l-sme. A detailed description of the algorithms underlying L-SME is available in [1]. © 2011 Springer-Verlag.
CITATION STYLE
Fassetti, F., Greco, G., & Terracina, G. (2011). L-SME: A system for mining loosely structured motifs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6913 LNAI, pp. 621–625). https://doi.org/10.1007/978-3-642-23808-6_42
Mendeley helps you to discover research relevant for your work.