Gene identification and analysis: an application of neural network-based information fusion

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Description

Identifying genes within large regions of uncharacterized DNA is a difficult undertaking and is currently the focus of many research efforts. We describe a gene localization and modeling system called GRAIL. GRAIL is a multiple sensor-neural network based system. It localizes genes in anonymous DNA sequence by recognizing gene features related to protein-coding slice sites, and then combines the recognized features using a neural network system. Localized coding regions are then optimally parsed into a gene mode. RNA polymerase II promoters can also be predicted. Through years of extensive testing, GRAIL consistently localizes about 90 percent of coding portions of ... continued below

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11 p.

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Matis, S.; Xu, Y.; Shah, M.B.; Mural, R.J.; Einstein, J.R. & Uberbacher, E.C. October 1, 1996.

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Description

Identifying genes within large regions of uncharacterized DNA is a difficult undertaking and is currently the focus of many research efforts. We describe a gene localization and modeling system called GRAIL. GRAIL is a multiple sensor-neural network based system. It localizes genes in anonymous DNA sequence by recognizing gene features related to protein-coding slice sites, and then combines the recognized features using a neural network system. Localized coding regions are then optimally parsed into a gene mode. RNA polymerase II promoters can also be predicted. Through years of extensive testing, GRAIL consistently localizes about 90 percent of coding portions of test genes with a false positive rate of about 10 percent. A number of genes for major genetic diseases have been located through the use of GRAIL, and over 1000 research laboratories worldwide use GRAIL on regular bases for localization of genes on their newly sequenced DNA.

Physical Description

11 p.

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OSTI as TI96015227

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  • Foundations of decision/information fusion workshop on applications to engineering problems, Washington, DC (United States), 7-9 Aug 1996

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  • Other: TI96015227
  • Report No.: CONF-9608120--2
  • Grant Number: AC05-96OR22464
  • DOI: 10.2172/390524 | External Link
  • Office of Scientific & Technical Information Report Number: 390524
  • Archival Resource Key: ark:/67531/metadc679936

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Office of Scientific & Technical Information Technical Reports

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  • October 1, 1996

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

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  • Jan. 22, 2016, 11:09 a.m.

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Matis, S.; Xu, Y.; Shah, M.B.; Mural, R.J.; Einstein, J.R. & Uberbacher, E.C. Gene identification and analysis: an application of neural network-based information fusion, report, October 1, 1996; Tennessee. (digital.library.unt.edu/ark:/67531/metadc679936/: accessed June 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.