title: Sequence similarity is more relevant than species specificity in probabilistic backtranslation.
abstract: BACKGROUND
  Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module. The degeneracy of the genetic code makes backtranslation potentially ambiguous since most amino acids are encoded by multiple codons. The common approach to overcome this difficulty is based on imitation of codon usage within the target species.
  
  
  RESULTS
  This paper describes EasyBack, a new parameter-free, fully-automated software for backtranslation using Hidden Markov Models. EasyBack is not based on imitation of codon usage within the target species, but instead uses a sequence-similarity criterion. The model is trained with a set of proteins with known cDNA coding sequences, constructed from the input protein by querying the NCBI databases with BLAST. Unlike existing software, the proposed method allows the quality of prediction to be estimated. When tested on a group of proteins that show different degrees of sequence conservation, EasyBack outperforms other published methods in terms of precision.
  
  
  CONCLUSIONS
  The prediction quality of a protein backtranslation methis markedly increased by replacing the criterion of most used codon in the same species with a Hidden Markov Model trained with a set of most similar sequences from all species. Moreover, the proposed method allows the quality of prediction to be estimated probabilistically.
authors.affiliation: Dipartimento di Matematica e Informatica, Università di Catania, Viale A, Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it
authors.forename: Alfredo
authors.initials: A
authors.lastname: Ferro
authors.forename: Rosalba
authors.initials: R
authors.lastname: Giugno
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Pigola
authors.forename: Alfredo
authors.initials: A
authors.lastname: Pulvirenti
authors.forename: Cinzia
authors.initials: C
authors.lastname: Di Pietro
authors.forename: Michele
authors.initials: M
authors.lastname: Purrello
authors.forename: Marco
authors.initials: M
authors.lastname: Ragusa
mesh_terms: D000465:Algorithms; D003062:Codon / Q000235:genetics*; D017124:Conserved Sequence / Q000235:genetics; D019143:Evolution, Molecular; D006801:Humans; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D014176:Protein Biosynthesis / Q000235:genetics*; D011506:Proteins / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods; D017386:Sequence Homology, Amino Acid; D012984:Software; D013045:Species Specificity
chemical_list: D003062:Codon; D011506:Proteins