Genes, information and sense: complexity and knowledge retrieval


Тип публикации: статья из журнала (материалы конференций, опубликованные в журналах)

Конференция: Annual European Conference on Complex Systems; Dresden, GERMANY; Dresden, GERMANY

Год издания: 2008

Идентификатор DOI: 10.1007/s12064-008-0032-1

Ключевые слова: frequency, dictionary, entropy, expected continuation, mutual entropy, information, codon usage, conference paper, functional status, genome, knowledge, nucleotide sequence, RNA splicing, semantics, statistical concepts, Algorithms, Base Sequence, Chromosome Mapping, Computational Biology, Computer Simulation, DNA, Information Storage and Retrieval, Models, Genetic, Molecular Sequence Data, Sequence Analysis, DNA, Structure-Activity Relationship

Аннотация: Information capacity of nucleotide sequences measures the unexpectedness of a continuation of a given string of nucleotides, thus having a sound relation to a variety of biological issues. A continuation is defined in a way maximizing the entropy of the ensemble of such continuations. The capacity is defined as a mutual entropy of Показать полностьюreal frequency dictionary of a sequence with respect to the one bearing the most expected continuations; it does not depend on the length of strings contained in a dictionary. Various genomes exhibit a multi-minima pattern of the dependence of information capacity on the string length, thus reflecting an order within a sequence. The strings with significant deviation of an expected frequency from the real one are the words of increased information value. Such words exhibit a non-random distribution alongside a sequence, thus making it possible to retrieve the correlation between a structure, and a function encoded within a sequence.

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Журнал: Theory in Biosciences

Выпуск журнала: Vol. 127, Is. 2

Номера страниц: 69-78

ISSN журнала: 14317613

Место издания: NEW YORK

Издатель: SPRINGER


  • Sadovsky M.G. (Institute of Computational Modelling of RAS)
  • Shchepanovsky A.S. (Institute of Computational Modelling of RAS)
  • Putintseva J.A. (Siberian Federal University)