Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a novel comparative method for the ab initio prediction of protein coding genes in eukaryotic genomes. The method simultaneously predicts the gene structures of two un-annotated input DNA sequences which are homologous to each other and retrieves the subsequences which are conserved beten the two DNA sequences. It is capable of predicting partial, complete and multiple genes and can align pairs of genes which differ by events of exon-fusion or exon-splitting. The method employs a probabilistic pair hidden Markov model.  generate annotations using our model with two different algorithms: the Viterbi algorithm in its linear memory implementation and a new heuristic algorithm, called the stepping stone algorithm, for which both memory and time requirements scale linearly with the sequence length.  have implemented the model in a computer program called DOUBLESCAN. In this article,  introduce the method and confirm the validity of the approach on a test set of 80 pairs of orthologous DNA sequences from mouse and human. More information can be found at: http://www.sanger.ac. uk/Software/analysis/doublescan/.
['Irmtraud M. Meyer', 'Richard Durbin']
I am writing a research paper on a idea Comparative ab initio prediction of gene structures using pair HMMs
[{"from": "human", "value": "I am writing a research paper on a idea Comparative ab initio prediction of gene structures using pair HMMs"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a novel comparative method for the ab initio prediction of protein coding genes in eukaryotic genomes. The method simultaneously predicts the gene structures of two un-annotated input DNA sequences which are homologous to each other and retrieves the subsequences which are conserved beten the two DNA sequences. It is capable of predicting partial, complete and multiple genes and can align pairs of genes which differ by events of exon-fusion or exon-splitting. The method employs a probabilistic pair hidden Markov model.  generate annotations using our model with two different algorithms: the Viterbi algorithm in its linear memory implementation and a new heuristic algorithm, called the stepping stone algorithm, for which both memory and time requirements scale linearly with the sequence length.  have implemented the model in a computer program called DOUBLESCAN. In this article,  introduce the method and confirm the validity of the approach on a test set of 80 pairs of orthologous DNA sequences from mouse and human. More information can be found at: http://www.sanger.ac. uk/Software/analysis/doublescan/."}]