The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The functional motifs composed of several sequential blocks are difficult to find. Current mining methods might individually find each motif block but fail to connect them with large irregular gaps. In this paper we propose a novel method for the efficient extraction of structured motifs from DNA sequences using multi-objective genetic algorithm. The main advantage of our approach is that a large...
This paper addresses the development of a plug and run wrapper to incorporate fuzziness into VRXQuery, the querying facility of VIREX which is a user-friendly system for transforming and querying relational data as XML. Our basic argument is not to force the underlying XML data to incorporate fuzziness. Rather, fuzziness is smoothly supported in a novel plug and run manner via a wrapper. Either the...
This paper presents a novel motif discovery algorithm based on multi-objective genetic algorithms to extract non-dominated motifs in DNA sequences. The main advantage of our approach is that a large number of tradeoff (non-dominated) motifs can be obtained by a single run with respect to conflicting objectives: similarity, motif length and support maximization. In this paper, the method extracts non-dominated...
It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining, simply because characteristics of quantitative data are in general unknown. Besides, it is unrealistic that the most appropriate fuzzy sets can always be provided by domain experts. Motivated by this, in this paper we propose an automated method...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.