Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Optimal spaced seeds re developed as a method to increase sensitivity of local alignment programs similar to BLASTN. Such seeds have been used before in the program PatternHunter, and have given improved sensitivity and running time relative to BLASTN in genome–genome comparison.  study the problem of computing optimal spaced seeds for detecting homologous coding regions in unannotated genomic sequences. By using ll-chosen seeds,  are able to improve the sensitivity of coding sequence alignment over that of TBLASTX, while keeping runtime comparable to BLASTN.  identify good seeds by first giving effective hidden Markov models of conservation in alignments of homologous coding regions.  give an efficient algorithm to compute the optimal spaced seed when conservation patterns are generated by these models. Our results offer the hope of improved gene finding due to fer missed exons in DNA/DNA comparison, and more effective homology search in general, and may have applications outside of bioinformatics.
['Brona Brejová', 'Daniel G. Brown', 'Tomas Vinar']
I am writing a research paper on a idea OPTIMAL SPACED SEEDS FOR HOMOLOGOUS CODING REGIONS
[{"from": "human", "value": "I am writing a research paper on a idea OPTIMAL SPACED SEEDS FOR HOMOLOGOUS CODING REGIONS"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Optimal spaced seeds re developed as a method to increase sensitivity of local alignment programs similar to BLASTN. Such seeds have been used before in the program PatternHunter, and have given improved sensitivity and running time relative to BLASTN in genome\u2013genome comparison.  study the problem of computing optimal spaced seeds for detecting homologous coding regions in unannotated genomic sequences. By using ll-chosen seeds,  are able to improve the sensitivity of coding sequence alignment over that of TBLASTX, while keeping runtime comparable to BLASTN.  identify good seeds by first giving effective hidden Markov models of conservation in alignments of homologous coding regions.  give an efficient algorithm to compute the optimal spaced seed when conservation patterns are generated by these models. Our results offer the hope of improved gene finding due to fer missed exons in DNA/DNA comparison, and more effective homology search in general, and may have applications outside of bioinformatics."}]