Browsing by Author "Leon, G"

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    cis recognition elements in plant mitochondrion RNA editing
    (2001) Farré, JC; Leon, G; Jordana, X; Araya, A
    RNA editing in higher plant mitochondria modifies mRNA sequences by means of C-to-U conversions at highly specific sites. To determine the cis elements involved in recognition of an editing site in plant mitochondria, deletion and site-directed mutation constructs containing the cognate cox II mitochondrial gene were introduced into purified mitochondria by electroporation. The RNA editing status was analyzed for precursor and spliced transcripts from the test construct. We found that only a restricted number of nucleotides in the vicinity of the target C residue were necessary for recognition by the editing machinery and that the nearest neighbor 3 ' residues were crucial for the editing process. We provide evidence that two functionally distinguishable sequences can be defined: the 16-nucleotide 5 ' region, which can be replaced with the same region from another editing site, and a 6-nucleotide 3 ' region specific to the editing site. The latter region may play a role in positioning the actual editing residue.
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    Using global search heuristics for the capacity vehicle routing problem
    (PERGAMON-ELSEVIER SCIENCE LTD, 1998) Rodriguez, P; Nussbaum, M; Baeza, R; Leon, G; Sepulveda, M; Cobian, A
    In this work, a Frame is posed which allows to define global search heuristics in an efficient and declarative way, which interacts with a specific computational implementation of a problem. An overview of different ways to solve problems by the use of global search is presented, followed by the specification of the language proposed. A real decision support system was developed through the use of the language. The problem faced was an extension of the capacity vehicle routing problem. The followed approach minimizes the development cost of a decision support system for logistic and productive environments, since the performance of different heuristics can be tested using the language in a straightforward way. Besides, when new requirements or additional knowledge about the problem appear, the solving engine can be easily modified through the heuristic language. (C) 1998 Elsevier Science Ltd All rights reserved.