Dr Leonardo de Oliveira Martins

Senior Researcher

Contact via email

Informatics and bioinformatics support

Epidemiology, genomics and antimicrobial resistance of bacteria

I am a computational biologist specialised in statistical genomics, particularly in Bayesian phylogenetics and phylogenomics. I am also interested in chemometrics, transcriptomics, and population genomics.

I have a PhD in Agricultural and Environmental Biology from the University of Tokyo (Japan), developing statistical models for recombination detection and phylogenetic dating. During my PhD I also worked with QTL analysis and protein structure prediction. I then did postdoctoral training at the University of Vigo (Spain), at the University of Lausanne (Switzerland), and at Imperial College London (UK). During this time I created models for species tree inference, phylogenomic statistical learning, and hyperspectral imaging analysis. I have studied the evolutionary history of several groups, from viruses, malaria, and marine species, to deep phylogenies like the tree of Eukaryotes or the whole tree of life.

Currently I develop and apply phylogenomic pipelines to large pangenomic data sets, aiming at facilitating interpretation and integration with other analyses.

Key Publications

  • L. de Oliveira Martins, D. Mallo, D. Posada (2016). “A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction”. Systematic Biology 65(3), 397-416 doi:10.1093/sysbio/syu082
  • D. Mallo, L. de Oliveira Martins, D. Posada (2016). “SimPhy: Phylogenomic Simulation of Gene, Locus and Species Trees”. Systematic Biology 65(2), 334-344 doi:10.1093/sysbio/syv082
  • L. de Oliveira Martins, D. Posada (2014). “Testing for Universal Common Ancestry”. Systematic Biology 63(5), 838-842 doi:10.1093/sysbio/syu041
  • L. de Oliveira Martins, D. Mallo, D. Posada (2013). “Phylogenetic Likelihood”. eLS. a0005141 doi:10.1002/9780470015902.a0005141
  • L de Oliveira Martins, H. Kishino (2010). “Distribution of distances between topologies and its effect ondetection of phylogenetic recombination”. Annals of the Institute of Statistical Mathematics 62 (1), 145-159 doi:10.1007/s10463-009-0259-8

Hansel C. S., Crowder S. W., Cooper S., Gopal S., João Pardelha da Cruz M., de Oliveira Martins L., Keller D., Rothery S., Becce M., Cass A. E. G., Bakal C., Chiappini C., Stevens M. M.. (2019)

Nanoneedle-Mediated Stimulation of Cell Mechanotransduction Machinery.

ACS nano, 13, 2913-2926


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de Oliveira Martins L., Page A. J., Mather A. E., Charles I. G.. (2019)

Taxonomic resolution of the ribosomal RNA operon in bacteria: Implications for its use with long-read sequencing

Nucleic Acids Research Genomics and Bioinformatics, 2, lqz016


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de Oliveira Martins L., Posada D.. (2016)

Infinitely long branches and an informal test of common ancestry.

Biology direct, 11, 19


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de Oliveira Martins L., Mallo D., Posada D.. (2016)

A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.

Systematic biology, 65, 397-416


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Mallo D., de Oliveira Martins L., Posada D.. (2016)

SimPhy: Phylogenomic Simulation of Gene, Locus, and Species Trees.

Systematic biology, 65, 334-44


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Mallo D., de Oliveira Martins L., Posada D.. (2014)

Unsorted homology within locus and species trees.

Systematic biology, 63, 988-92


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de Oliveira Martins L., Posada D.. (2014)

Testing for universal common ancestry.

Systematic biology, 63, 838-42


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Bizinoto M. C., Yabe S., Leal É., Kishino H., de Oliveira Martins L., de Lima M. L., Morais E. R., Diaz R. S., Janini L. M.. (2013)

Codon pairs of the HIV-1 vif gene correlate with CD4+ T cell count.

BMC infectious diseases, 13, 173


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