Las Vegas algorithms for gene recognition: Suboptimal and error-tolerant spliced alignment

Conference · Mon Dec 01 00:00:00 EST 1997

OSTI ID:549029

Sze, Sing-Hoi; Pevzner, P A ^[1]

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1. Univ. of Southern California, Los Angeles, CA (United States)

Recently, Gelfand, Mironov and Pevzner proposed a spliced alignment approach to gene recognition that provides 99% accurate recognition of human gene if a related mammalian protein is available. However, even 99% accurate gene predictions are insufficient for automated sequence annotation in large-scale sequencing projects and therefore have to be complemented by experimental gene verification. 100% accurate gene predictions would lead to a substantial reduction of experimental work on gene identification. Our goal is to develop an algorithm that either predicts an exon assembly with accuracy sufficient for sequence annotation or warns a biologist that the accuracy of a prediction is insufficient and further experimental work is required. We study suboptimal and error-tolerant spliced alignment problems as the first steps towards such an algorithm, and report an algorithm which provides 100% accurate recognition of human genes in 37% of cases (if a related mammalian protein is available). For 52% of genes, the algorithm predicts at least one exon with 100% accuracy. 30 refs., 1 fig., 3 tabs.

• Research Organization: Association for Computing Machinery, New York, NY (United States); Sloan (Alfred P.) Foundation, New York, NY (United States)
• DOE Contract Number: FG02-94ER61919
• OSTI ID: 549029
• Report Number(s): CONF-970137-; TRN: 97:005298-0041
• Resource Relation: Conference: RECOMB `97: 1. annual conference on research in computational molecular biology, Santa Fe, NM (United States), 20-22 Jan 1997; Other Information: PBD: 1997; Related Information: Is Part Of RECOMB 97. Proceedings of the first annual international conference on computational molecular biology; PB: 370 p.
• Country of Publication: United States
• Language: English

Related Subjects

55 BIOLOGY AND MEDICINE
BASIC STUDIES
99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
ALGORITHMS
ACCURACY
GENES
GENETIC MAPPING
VERIFICATION
SPLICING
CORRELATIONS
DNA SEQUENCING
AUTOMATION
MATHEMATICAL MODELS
PROTEINS
AMINO ACID SEQUENCE
MOLECULAR BIOLOGY
MAMMALS
EXONS
NUCLEOTIDES
ERRORS
DATA