Juan A G Ranea

Summary

Affiliation: University College London
Country: UK

Publications

  1. ncbi Microeconomic principles explain an optimal genome size in bacteria
    Juan A G Ranea
    Biomolecular Structure and Modelling Group, Department of Biochemistry and Molecular Biology, University College London, London, UK
    Trends Genet 21:21-5. 2005
  2. ncbi Predicting protein function with hierarchical phylogenetic profiles: the Gene3D Phylo-Tuner method applied to eukaryotic genomes
    Juan A G Ranea
    Department of Biochemistry and Molecular Biology, University College London, London, United Kingdom
    PLoS Comput Biol 3:e237. 2007
  3. ncbi Protein superfamily evolution and the last universal common ancestor (LUCA)
    Juan A G Ranea
    Biomolecular Structure and Modelling Group, Department of Biochemistry and Molecular Biology, University College London, London, WC1E 6BT, UK
    J Mol Evol 63:513-25. 2006
  4. ncbi Exploiting protein structure data to explore the evolution of protein function and biological complexity
    Russell L Marsden
    Department of Biochemistry, University College London Gower Street, London WC1E 6BT, UK
    Philos Trans R Soc Lond B Biol Sci 361:425-40. 2006
  5. ncbi Evolution of protein superfamilies and bacterial genome size
    Juan A G Ranea
    Biomlolecular Structure and Modelling Group, Department of Biochemistry and Molecular Biology, University College London, London WC1E 6BT, UK
    J Mol Biol 336:871-87. 2004
  6. ncbi Assessing protein co-evolution in the context of the tree of life assists in the prediction of the interactome
    Florencio Pazos
    Structural Bioinformatics Group, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK
    J Mol Biol 352:1002-15. 2005

Detail Information

Publications7

  1. ncbi Microeconomic principles explain an optimal genome size in bacteria
    Juan A G Ranea
    Biomolecular Structure and Modelling Group, Department of Biochemistry and Molecular Biology, University College London, London, UK
    Trends Genet 21:21-5. 2005
    ..This optimum is reached when the bacterial genome obtains the maximum metabolic complexity (revenue) for minimal regulatory genes (logistic cost)...
  2. ncbi Predicting protein function with hierarchical phylogenetic profiles: the Gene3D Phylo-Tuner method applied to eukaryotic genomes
    Juan A G Ranea
    Department of Biochemistry and Molecular Biology, University College London, London, United Kingdom
    PLoS Comput Biol 3:e237. 2007
    ..Our method finds functional relationships that are not detectable by the conventional presence-absence profile comparisons, and it does not require a priori any fixed criteria to define orthologous genes...
  3. ncbi Protein superfamily evolution and the last universal common ancestor (LUCA)
    Juan A G Ranea
    Biomolecular Structure and Modelling Group, Department of Biochemistry and Molecular Biology, University College London, London, WC1E 6BT, UK
    J Mol Evol 63:513-25. 2006
    ....
  4. ncbi Exploiting protein structure data to explore the evolution of protein function and biological complexity
    Russell L Marsden
    Department of Biochemistry, University College London Gower Street, London WC1E 6BT, UK
    Philos Trans R Soc Lond B Biol Sci 361:425-40. 2006
    ....
  5. ncbi Evolution of protein superfamilies and bacterial genome size
    Juan A G Ranea
    Biomlolecular Structure and Modelling Group, Department of Biochemistry and Molecular Biology, University College London, London WC1E 6BT, UK
    J Mol Biol 336:871-87. 2004
    ..For the size-dependent superfamilies, linearly distributed superfamilies are involved mainly in metabolism, and non-linearly distributed superfamily domains are involved principally in gene regulation...
  6. ncbi Assessing protein co-evolution in the context of the tree of life assists in the prediction of the interactome
    Florencio Pazos
    Structural Bioinformatics Group, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK
    J Mol Biol 352:1002-15. 2005
    ..We also show that taking into account these non-canonical evolutionary events when assessing the similarity between evolutionary trees improves the performance of the method predicting interactions...