A new approach for gene prediction using comparative sequence analysis

Rong Chen, Hesham H. Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The availability of large fragments of genomic DNA makes it possible to apply comparative genomics for identification of protein-coding regions. In this work, a comparative analysis is conducted on homologous genomic sequences of organisms with different evolutionary distances and the conservation of the noncoding regions between closely related organisms is found. In contrast, more distance shows much less intron similarity but less conservation on the exon structures. This study sought to illuminate the impact of evolutionary distances on the performance of the proposed gene-finding program based on the cross-species sequence comparison. Base on the finding from comparative study and training of data sets, we proposed a model by which coding sequence could be identified by comparing sequences of multiple species, both close and approximately distant. The reliability of the proposed method is evaluated in terms of sensitivity and specificity, and results are compared to those obtained by other popular gene prediction programs. Provided sequences can be found from other species at appropriate evolutionary distances, this approach could be applied in newly sequenced organisms where no species-dependent statistical models are available.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM Symposium on Applied Computing
Number of pages8
StatePublished - 2005
Event20th Annual ACM Symposium on Applied Computing - Santa Fe, NM
Duration: Mar 13 2005Mar 17 2005


Other20th Annual ACM Symposium on Applied Computing
CitySanta Fe, NM


  • Coding and non-coding regions
  • Comparative genomics
  • Gene prediction
  • Multiple species

ASJC Scopus subject areas

  • General Computer Science


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