Literature DB >> 11673235

DIANA-EST: a statistical analysis.

A G Hatzigeorgiou1, P Fiziev, M Reczko.   

Abstract

MOTIVATION: 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.
RESULTS: 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. AVAILABILITY: The program is available upon request from the author. CONTACT: Present address: Department of Genetics, University of Pennsylvania, School of Medicine, 475 Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA 19104-6145, USA. artemis@pcbi.upenn.edu.

Mesh:

Substances:

Year:  2001        PMID: 11673235     DOI: 10.1093/bioinformatics/17.10.913

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  13 in total

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Review 6.  Differentiating protein-coding and noncoding RNA: challenges and ambiguities.

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9.  prot4EST: translating expressed sequence tags from neglected genomes.

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10.  On the extent and origins of genic novelty in the phylum Nematoda.

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