Improved orthologous databases to ease protozoan targets inference

Background: homology inference helps on identifying similarities,as well as differences among organisms,which provides a better insight on how closely related one might be to another. in addition,comparative genomics pipelines are widely adopted tools designed using different bioinformatics applications and algorithms. in this article,we propose a methodology to build improved orthologous databases with the potential to aid on protozoan target identification,one of the many tasks which benefit from comparative genomics tools. methods: our analyses are based on orthosearch,a comparative genomics pipeline originally designed to infer orthologs through protein-profile comparison,supported by an hmm,reciprocal best hits based approach. our methodology allows orthosearch to confront two orthologous databases and to generate an improved new one. such can be later used to infer potential protozoan targets through a similarity analysis against the human genome. results: the protein sequences of cryptosporidium hominis,entamoeba histolytica and leishmania infantum genomes were comparatively analyzed against three orthologous databases: (i) eggnog kog,(ii) protozoadb and (iii) kegg orthology (ko). that allowed us to create two new orthologous databases,ko + eggnog kog and ko + eggnog kog + protozoadb