We are centered in understand the gene regulation and metabolism including computational approaches. In this regard, our work on Gene regulation involves the analysis of DNA-binding transcription factors in Archaea and Bacteria cellular domains. Our approach considers the identification of TFs by the design of family-specific HMM models and by the search with models deposited in diverse databases. We have identified and evaluated the repertories of TFs in three bacterial models: Escherichia coli K12 , Bacillus subtilis 168 , and Staphylococcus aureus .
In addition, we explore the use of network approaches to analyze the evolution of metabolism. From this perspective and using large-scale genomic and bioinformatics tools, eleven different amino acid pathways have been proposed as ancestral to bacteria, archaea, and eukarya, closer to the last common ancestor. We also suggested that Metabolic Pathways have evolved by the recruitment of blocks of enzymes sharing similar catalytic activities.
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