Locating protein-coding regions in human DNA sequences by a multiple sensor-neural network approach
- Oak Ridge National Lab., TN (United States) Univ. of Tennessee, Oak Ridge (United States)
Genes in higher eukaryotes may span tens or hundreds of kilobases with the protein-coding regions accounting for only a few percent of the total sequence. Identifying genes within large regions of uncharacterized DNA is a difficult undertaking and is currently the focus of many research efforts. The authors describe a reliable computational approach for locating protein-coding portions of genes in anonymous DNA sequence. Using a concept suggested by robotic environmental sensing, the authors method combines a set of sensor algorithms and a neural network to localize the coding regions. Several algorithms that report local characteristics of the DNA sequence, and therefore act as sensors, are also described. In its current configuration the coding recognition module identifies 90% of coding exons of length 100 bases or greater with less than one false positive coding exon indicated per five coding exons indicated. This is a significantly lower false positive rate than any method of which the authors are aware. This module demonstrates a method with general applicability to sequence-pattern recognition problems and is available for current research efforts.
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 5604872
- Journal Information:
- Proceedings of the National Academy of Sciences of the United States of America; (United States), Vol. 88:24; ISSN 0027-8424
- Country of Publication:
- United States
- Language:
- English
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GENES
MOLECULAR STRUCTURE
ALKALINE PHOSPHATASE
BIOLOGICAL MARKERS
DNA SEQUENCING
MAN
PATTERN RECOGNITION
PHOSPHORUS-GROUP TRANSFERASES
PHOSPHOTRANSFERASES
PROTEINS
PROTHROMBIN
ANIMALS
BLOOD COAGULATION FACTORS
COAGULANTS
DRUGS
ENZYMES
ESTERASES
HEMATOLOGIC AGENTS
HYDROLASES
MAMMALS
ORGANIC COMPOUNDS
PHOSPHATASES
PRIMATES
STRUCTURAL CHEMICAL ANALYSIS
TRANSFERASES
VERTEBRATES
550200* - Biochemistry