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An artificial intelligence approach to DNA sequence feature recognition.
Mural, R J; Einstein, J R; Guan, X; Mann, R C; Uberbacher, E C.
Afiliación
  • Mural RJ; Biology Division, Oak Ridge National Laboratory, TN 37831-8077.
Trends Biotechnol ; 10(1-2): 66-9, 1992.
Article en En | MEDLINE | ID: mdl-1367939
The ultimate goal of the Human Genome project is to extract the biologically relevant information recorded in the estimated 100,000 genes encoded by the 3 x 10(9) bases of the human genome. This necessitates development of reliable computer-based methods capable of analysing and correctly identifying genes in the vast amounts of DNA-sequence data generated. Such tools may save time and labour by simplifying, for example, screening of cDNA libraries. They may also facilitate the localization of human disease genes by identifying candidate genes in promising regions of anonymous DNA sequence.
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Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ADN / Inteligencia Artificial / Secuencia de Bases Idioma: En Revista: Trends Biotechnol Año: 1992 Tipo del documento: Article Pais de publicación: Reino Unido
Buscar en Google
Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ADN / Inteligencia Artificial / Secuencia de Bases Idioma: En Revista: Trends Biotechnol Año: 1992 Tipo del documento: Article Pais de publicación: Reino Unido