Structural Bioinformatics

Cristina Marino Buslje - Fundación Instituto Leloir

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Structural Bioinformatics

The structure and function of proteins is crucial to understand all biological processes. The principal interest of our group is the study of proteins, including their function, evolution, structure and interaction with other molecules. Our focus is the study and development of bioinformatics tools for analysis and prediction of functionally important sites, classification and functional annotation of proteins as well as protein-protein interactions.

See our tools

  • Residues coevolution networks analysis.
  • Protein-protein interaction prediction.
  • Superfamily classification into proteins functional families.
  • Protein coevolution.
  • Development of bioinformatics tools for protein analysis.

Simonetti FL, Tornador C, Nabau-Moretó N, Molina-Vila MA, Marino-Buslje C. Kin-Driver: a database of driver mutations in protein kinases. Database: The Journal of Biological Databases and Curation. (2014).doi:10.1093/database/bau104. PubMed

Iserte J, Simonetti FL, Zea DJ, Teppa E, Marino-Buslje C.I-COMS: Interprotein-COrrelated Mutations Server.(2015) Nucleic Acids Res. PubMed

Teppa, E., Wilkins, A.D., Nielsen, M., Marino Buslje, C. Disentangling evolutionary signals: Conservation, specificity determining positions and coevolution. Implication for catalytic residue prediction. (2012) BMC Bioinformatics, p. 235. PubMed

Aguilar, D., Oliva, B., Marino Buslje, C. Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features. (2012) PLoS ONE, 7 (7), art. no. e41430, . PubMed

Chemes, L.B., Glavina, J., Alonso, L.G., Marino-Buslje, C., de Prat-Gay, G., Sánchez, I.E. Sequence Evolution of the Intrinsically Disordered and Globular Domains of a Model Viral Oncoprotein. (2012) PLoS ONE, 7 (10), art. no. e47661 PubMed

Marino Buslje, C., Teppa, E., Di Doménico, T., Delfino, J.M., Nielsen, M. Networks of high mutual information define the structural proximity of catalytic sites: implications for catalytic residue identification. (2010) PLoS computational biology, 6 (11) PubMed

Buslje, C.M., Santos, J., Delfino, J.M., Nielsen, M. Correction for phylogeny, small number of observations and data redundancy improves the identification of coevolving amino acid pairs using mutual information. (2009) Bioinformatics, 25 (9), pp. 1125-113 PubMed





Cristina Marino Buslje
Head of Bioinformatics Unit - cmb@leloir.org.ar



Javier Iserte
PhD CONICET



Elin Teppa
Assistant researcher -Licencia



Elizabeth Martinez Pérez
Doctoral Fellow- AGENCIA



Fernando Ezequiel Orti
Doctoral Fellow - CONICET



Maximiliano Castillo
Undergraduate Student