• Research interests

    Bioinformatics, Artificial Intelligence and Data Analysis

    • Development of new unsupervised and supervised machine learning methods
    • Use of machine learning methods, including clustering and deep learning, for the analysis of biological and biomedical data
    • Phylogenetic analysis
    • Genomics
    • Evolution and origin of SARS-CoV-2
    • Analysis of CRISPR/CAS9 data
    • Analysis of High Throughput Screening (HTS) data
    My current research also involves the development of an automated recommendation system based on deep learning to recommend the best clustering algorithm for a given input dataset. Additionally, I am working on creating a generic machine learning model to define the concept of a cluster, and comparing various auto-encoding approaches and clustering algorithms to achieve better clustering results.

  • Professor
    Vladimir Makarenkov
    Full professor / Professeur titulaire
    Director of DESS in Bioinformatics at UQAM
    Département d'Informatique, Université du Québec à Montréal (UQAM)
    Regular member of LaCIM and affiliate member of Mila


    CV and publications

  • Latest publications

    For the complete list of publications, please see my Google Scholar profile

  • Developed software

    T-REX web server (link) The T-REX (tree and reticulogram reconstruction) web server allows the users to perform several popular methods of phylogenetic analysis as well as some new phylogenetic algorithms for inferring, drawing and statistical validation of phylogenetic trees and networks
    SimPlot++ (link) Multi-platform application for representing sequence similarity and detecting recombination
    DuneScan (link) Deep uncertainty estimation for skin cancer (DuneScan web server)
    CRISPR-Cas9 (data and program repository) (link) CRISPR-Cas9 benchmark data and program repository for on- and off-target experiments
    Armadillo workflow platform (link) Armadillo is a workflow platform dedicated to phylogenetic as well as general bioinformatics analysis. A number of important computational biology tools have been included in the first release. The Armadillo platform is open-source and allows users to develop their own modules and/or integrate existing computer applications
    HTS Corrector (link) HTS Corrector software is designed to examine and visualize HTS data and correct experimental HTS assays
    Optimal Variable Weighting (link) Optimal variable weighting for ultrametric and additive clustering and k-means partitioning (with Pierre Legendre, Université de Montréal)
    Linear and Polynomial RDA and CCA (link) Linear and polynomial canonical analysis (with Pierre Legendre, Université de Montréal)
    Robinson and Foulds distance (link) Program for computation of the Robinson and Foulds topological distance between two phylogenetic trees (with Pierre Legendre, Université de Montréal)