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

Abstract

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.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Oak Ridge National Lab., TN (United States)
Sponsoring Org.:
USDOE Office of Energy Research, Washington, DC (United States)
OSTI Identifier:
390524
Report Number(s):
CONF-9608120-2
ON: TI96015227
DOE Contract Number:  
AC05-96OR22464
Resource Type:
Technical Report
Resource Relation:
Conference: Foundations of decision/information fusion workshop on applications to engineering problems, Washington, DC (United States), 7-9 Aug 1996; Other Information: PBD: [1996]
Country of Publication:
United States
Language:
English
Subject:
55 BIOLOGY AND MEDICINE, BASIC STUDIES; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; DNA SEQUENCING; NEURAL NETWORKS; RESEARCH PROGRAMS; GENES; PROTEINS; INTERNET; ALGORITHMS; CODONS; RNA; SPLICING

Citation Formats

Matis, S, Xu, Y, Shah, M B, Mural, R J, Einstein, J R, and Uberbacher, E C. Gene identification and analysis: an application of neural network-based information fusion. United States: N. p., 1996. Web. doi:10.2172/390524.
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. United States. doi:10.2172/390524.
Matis, S, Xu, Y, Shah, M B, Mural, R J, Einstein, J R, and Uberbacher, E C. Tue . "Gene identification and analysis: an application of neural network-based information fusion". United States. doi:10.2172/390524. https://www.osti.gov/servlets/purl/390524.
@article{osti_390524,
title = {Gene identification and analysis: an application of neural network-based information fusion},
author = {Matis, S and Xu, Y and Shah, M B and Mural, R J and Einstein, J R and Uberbacher, E C},
abstractNote = {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.},
doi = {10.2172/390524},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1996},
month = {10}
}