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PMID: 11673235 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

DIANA-EST: a statistical analysis.

Bioinformatics (Oxford, England) ·Vol. 17 ·No. 10 ·2001-10-00 ·Pages 913-9

Hatzigeorgiou AG, Fiziev P, Reczko M

Abstract

Expressed Sequence Tags (ESTs) are next to cDNA sequences as the most direct way to locate in silico the genes of the genome and determine their structure. Currently ESTs make up more than 60% of all the database entries. The goal of this work is the development of a new program called DNA Intelligent Analysis for ESTs (DIANA-EST) based on a combination of Artificial Neural Networks (ANN) and statistics for the characterization of the coding regions within ESTs and the reconstruction of the encoded protein. 89.7% of the nucleotides from an independent test set with 127 ESTs were predicted correctly as to whether they are coding or non coding. The program is available upon request from the author. Present address: Department of Genetics, University of Pennsylvania, School of Medicine, 475 Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA 19104-6145, USA. [email protected].

MeSH Terms
Computational Biology Consensus Sequence DNA, Complementary/genetics Expressed Sequence Tags Neural Networks, Computer Sequence Analysis, DNA/statistics & numerical data Software
Chemicals
DNA, Complementary
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Hatzigeorgiou A G
Metagen GmbH, Ihnestr.63, 14195 Berlin, Germany. [email protected]
Fiziev P
Reczko M
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2001-10-00
Pages
913-9
Language
English
Region
England
NLM ID
9808944
Subset
IM
Analysis Services
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