SURVEY AND SUMMARY: Current methods of gene prediction, their strengths and weaknesses
AUTOR(ES)
Mathé, Catherine
FONTE
Oxford University Press
RESUMO
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.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=140543Documentos Relacionados
- SURVEY AND SUMMARY: Structures of trinucleotide repeats in human transcripts and their functional implications
- Strengths and weaknesses of EST-based prediction of tissue-specific alternative splicing
- SURVEY AND SUMMARY: Structural classification of zinc fingers
- SURVEY AND SUMMARY: The pre-ribosomal network
- SURVEY AND SUMMARY: The non-Watson–Crick base pairs and their associated isostericity matrices