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Gene finding for the helical cytokines
Darrell Conklin1, Betty Haldeman, Zeren Gao
1Department of Computing, City University, London, UK. conklin@city.ac.uk
Bioinformatics (Oxford, England)
|January 22, 2005
Summary
This study introduces a novel genomic threading algorithm that unifies gene finding and protein fold recognition. This approach enhances the discovery of evolutionarily divergent protein families by identifying conserved structural signals.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Gene finding remains challenging post-human genome sequencing.
- Current methods lack sensitivity for divergent protein families, requiring accurate exon assemblies for fold recognition.
- Evolutionary divergence can obscure sequence homology but conserve structural signals.
Purpose of the Study:
- To develop a new genomic threading algorithm.
- To integrate gene finding and fold recognition into a single process.
- To improve the identification of evolutionarily divergent protein families.
Main Methods:
- A novel genomic threading algorithm is presented.
- The method integrates gene finding and fold recognition.
- It identifies conserved intron/exon structures and structural element placements.
Main Results:
- The algorithm was validated on helical cytokines using cross-validation.
- It was applied to intergenic regions of the human genome.
- Two novel genes were discovered and are discussed.
Conclusions:
- The new algorithm successfully integrates gene finding and fold recognition.
- It is effective for identifying genes in evolutionarily divergent protein families.
- This method aids in discovering novel genes within the human genome.