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Applied bioinformatics for the identification of regulatory elements
- Source :
- Nature reviews. Genetics. 5(4)
- Publication Year :
- 2004
-
Abstract
- The compilation of multiple metazoan genome sequences and the deluge of large-scale expression data have combined to motivate the maturation of bioinformatics methods for the analysis of sequences that regulate gene transcription. Historically, these bioinformatics methods have been plagued by poor predictive specificity, but new bioinformatics algorithms that accelerate the identification of regulatory regions are drawing disgruntled users back to their keyboards. However, these new approaches and software are not without problems. Here, we introduce the purpose and mechanisms of the leading algorithms, with a particular emphasis on metazoan sequence analysis. We identify key issues that users should take into consideration in interpreting the results and provide an online training example to help researchers who wish to test online tools before taking an independent foray into the bioinformatics of transcription regulation.
- Subjects :
- Models, Genetic
Transcription, Genetic
business.industry
Sequence analysis
Genome, Human
Computational Biology
Phylogenetic footprinting
Biology
Regulatory Sequences, Nucleic Acid
Bioinformatics
Key issues
Genome
Software
Expression data
Genetics
Humans
Human genome
business
Promoter Regions, Genetic
Molecular Biology
Genetics (clinical)
Analysis method
Subjects
Details
- ISSN :
- 14710056
- Volume :
- 5
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Nature reviews. Genetics
- Accession number :
- edsair.doi.dedup.....3dc188d5f85ac2b79a06f667ae6f6053