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    A method for building simple physical models: representing the structures of nucleic acid

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    An improved low-resoln. phys. model for representing the structures of nucleic acids in presented. The models are inexpensive and easy to construct and show flexibility in application

    A graph-topological approach to recognition of pattern and similarity in RNA secondary structures

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    Secondary and tertiary RNA structures play an important role in many biological processes. Therefore the necessity arises to find similar higher-order structures for different but functionally homologous RNA sequences. We propose here a graph-topological approach to the problem, which shows two main features: simplified graph representation which allows the recognition of similarity of RNA secondary structures with the same branching look despite minor differences. This allows comparison among foldings from different sequences, and "pruning" of the secondary structures not shared by all the sequences since the early stages of the search. (b) The graph representation is encoded by the Randić topological index, and the search for the folding similarity is reduced to checking the identity of single numbers. These characteristics make this approach significantly different, less depending on empirical criteria, and less computationally heavy then previous methods, where the folding consensus has been measured by an alignment procedure or correlation of strings representing the secondary structures. Some U2 snRNA and viroid sequences are studied by this approach, which is imbedded in our previous search method based on genetic algorithms

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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