Current methods of gene prediction, their strengths and weaknesses.
Nucleic Acids Res
; 30(19): 4103-17, 2002 Oct 01.
Article
em En
| MEDLINE
| ID: mdl-12364589
ABSTRACT
While the genomes of many organisms have been sequenced over the last few years, transforming such raw sequence data into knowledge remains a hard task. A great number of prediction programs have been developed that try to address one part of this problem, which consists of locating the genes along a genome. This paper reviews the existing approaches to predicting genes in eukaryotic genomes and underlines their intrinsic advantages and limitations. The main mathematical models and computational algorithms adopted are also briefly described and the resulting software classified according to both the method and the type of evidence used. Finally, the several difficulties and pitfalls encountered by the programs are detailed, showing that improvements are needed and that new directions must be considered.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Genoma
/
Biologia Computacional
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Nucleic Acids Res
Ano de publicação:
2002
Tipo de documento:
Article
País de afiliação:
França