Curriculum Vitae of Vladimir Makarenkov



Born: October 17, 1970 in Moscow (Russia)

Spoken and written languages: English, French and Russian (native)


Studies and Graduations

Work Experience


Publications

Refereed journal publications

Lord, E., Willems, M., Lapointe, FJ. and Makarenkov, V. (2017), Using the stability of objects to determine the number of clusters in datasets, Information Sciences, 393, 29-46.

de Amorim, R.C., Shestakov, A., Mirkin, B. and Makarenkov, V. (2017), The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning, Pattern Recognition, 67, 62-72.

Willems, M., Lord, E., Laforest, L., Labelle, G., Lapointe, FJ., Di Sciullo, AM. and Makarenkov, V. (2016), Using hybridization networks to retrace the evolution of Indo-European languages, BMC Evolutionary Biology, 2016, 16:180.

de Amorim, R.C., Makarenkov, V. and Mirkin, B. (2016), A-Ward_pβ: Effective hierarchical clustering using the Minkowski metric and a fast k-means initialisation, Information Sciences, 370, 343-354.

Lord, E., Le Cam, M., Bapteste, E., Méheust, R., Makarenkov, V. and Lapointe, FJ. (2016), BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts, PloS one 11 (8), e0161474.

de Amorim, R.C. and Makarenkov, V. (2016), Applying subclustering and Lp distance in weighted K-means with distributed centroids, Neurocomputing, 173 (3), 700-707.

Caraus, I., Alsuwailem, A., Nadon, R. and Makarenkov, V. (2015), Detecting and overcoming systematic bias in high-throughput screening technologies: a comprehensive review of practical issues and methodological solutions, Briefings in Bioinformatics, 16 (6), 974-986.

Layeghifard, M., Makarenkov, V. and Peres-Neto P. (2015), Spatial and species compositional networks for inferring connectivity patterns in ecological communities, Global Ecology and Biogeography, 24 (6), 718-727.

Lord, E., Diallo, A. B. and Makarenkov, V. (2015), Classification of bioinformatics workflows using weighted versions of partitioning and hierarchical clustering algorithms, BMC Bioinformatics, 16:68, doi:10.1186/s12859-015-0508-1.

Willems, M., Tahiri, N. and Makarenkov, V. (2014), A new efficient algorithm for inferring explicit hybridization networks following the Neighbor-Joining principle, Journal of Bioinformatics and Computational Biology, 12(5), DOI: 10.1142/S0219720014500243.

Szathmary, L., Valtchev, V., Napoli, A., Godin, R., Boc, A. and Makarenkov, V. (2014), A fast compound algorithm for mining generators, closed itemsets, and computing links between equivalence classes, Annals of Mathematics and Artificial Intelligence, 70 (1-2), 81-105.

Layeghifard, M., Peres-Neto P. and Makarenkov, V. (2013), Inferring explicit weighted consensus networks to represent alternative evolutionary histories, BMC Evolutionary Biology, 13:274.

Boc, A., Diallo, Alpha B. and Makarenkov, V. (2012), T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks, Nucleic Acids Research, 40, Web Server issue, W573–W579.

Dragiev, P., Nadon, R. and Makarenkov, V. (2012), Two effective methods for correcting experimental high-throughput screening data, Bioinformatics, 28 (13), 1775–1782.

Layeghifard, M., Peres-Neto P. and Makarenkov, V. (2012), Using directed phylogenetic networks to retrace species dispersal history, Molecular Phylogenetics and Evolution, 64 (1), 190–197.

Lord, E., Leclercq M., Boc, A., Diallo, A. B. and Makarenkov, V. (2012), Armadillo 1.1: An original workflow platform for designing and conducting phylogenetic analysis and simulations, PLoS ONE, 7(1): e29903.

Boc, A. and Makarenkov, V. (2011), Towards an accurate identification of mosaic genes and partial horizontal gene transfers, Nucleic Acids Research, 39(21):e144.

Badescu, D., Boc. A., Diallo, A. B., and Makarenkov, V. (2011), Detecting genomic regions associated with a disease using variability functions and Adjusted Rand Index, BMC Bioinformatics, 12(Suppl 9):S9.

Dragiev, P., Nadon, R. and Makarenkov, V. (2011), Systematic error detection in experimental high-throughput screening, BMC Bioinformatics, 12:25.

Boc, A., Philippe, H. and Makarenkov, V. (2010), Inferring and validating horizontal gene transfer events using bipartition dissimilarity, Systematic Biology, 59: 195-211.

Makarenkov, V., Boc, A., Xie, J., Pers-Neto P., Lapointe, F.-J. and Legendre, P. (2010). Weighted bootstrapping: a correction method for assessing the robustness of phylogenetic trees, BMC Evolutionary Biology, 10:250.

Mballo, C. and Makarenkov, V. (2010). Using machine learning methods to predict experimental high-throughput screening data, Combinatorial Chemistry & High Throughput Screening, 13(5):430-441.

Diallo, A.B., Makarenkov, V. and Blanchette, M. (2010), Ancestors 1.0: A Web Server For Ancestral Sequence Reconstruction, Bioinformatics, 26(1):130-1.

Diallo, A.B., Badescu, D., Blanchette, M. and Makarenkov, V. (2009), A whole genome study and identification of specific carcinogenic regions of the Human Papilloma Viruses, Journal of Computational Biology, 16(10), 1461-1473.

Devloo V. and Makarenkov, V. (2008), Determination of genetic subnetworks relevant to a particular biological function: a logical analysis approach, in Progress in Mathematical Biology Research, Nova Science Publisher, 247-264.

Glazko, G., Makarenkov. V., Liu, J. and Mushegian, A. (2007), Evolutionary history of bacteriophages with double-stranded DNA genomes, Biology Direct, 2007, 2:36.

Makarenkov, V., Zentilli, P., Kevorkov, D., Gagarin, A., Malo, N. and Nadon R. (2007), An efficient method for the detection and elimination of systematic error in high-throughput screening, Bioinformatics, 23, 1648-1657.

Diallo, A.B., Makarenkov, V. and Blanchette, M (2007), Exact and Heuristic Method to the Indels Maximum Likelihood Problem, Journal of Computational Biology, 2007, 14, 446-461.

Gagarin, A., Makarenkov, V. and Zentilli, P. (2006), Using clustering techniques to improve hit selection in high-throughput screening, Journal of Biomolecular Screening, 11, 903-914.

Makarenkov, V., Kevorkov, D., Zentilli, P., Gagarin, A., Malo, N. and Nadon R. (2006), HTS-Corrector: New application for statistical analysis and correction of experimental data, Bioinformatics, 22, 1408-1409.

Makarenkov, V., Kevorkov, D. and Legendre, P. (2006), Phylogenetic Network Reconstruction Approaches, Applied Mycology and Biotechnology, International Elsevier Series, vol. 6. Bioinformatics, 61-97.

Diallo, A., Makarenkov, V. and Lapointe, F-J. (2006), A new effective method for estimating missing values in the sequence data prior to phylogenetic analysis, Evolutionary Bioinformatics, 2, 237–246.

Kevorkov, D. and Makarenkov, V. (2005), Statistical analysis of systematic errors in high-throughput screening, Journal of Biomolecular Screening, 10, 557-567.

Makarenkov, V. and Lapointe, F-J. (2004), A weighted least-squares approach for inferring phylogenies from incomplete distance matrices, Bioinformatics, 20, 2113-2121.

Makarenkov, V. and Legendre, P. (2004), From a phylogenetic tree to a reticulated network, Journal of Computational Biology, 11 (1), 195-212.

Makarenkov, V., Legendre, P. and Desdevises, Y. (2004), Modeling phylogenetic relationships using reticulated networks. Zoologica Scripta, 33 (1), 89-96.

Guenoche, A., Leclerc, B. and Makarenkov, V. (2004), On the extension of a partial metric to a tree metric (abstract available), Discrete Mathematics, 276, (1-3), 229-248.

Levasseur, C., Landry, P. A., Makarenkov, V., Kirsch, J. A. W. and Lapointe, F.-J. (2003), Trees from incomplete distance matrices: should missing distances be estimated or omitted?, Molecular Phylogenetics and Evolution.

Legendre, P. and Makarenkov, V. (2002), Reconstruction of biogeographic and evolutionary networks using reticulograms, Systematic Biology, 51(2), 199-216.

Makarenkov, V. and Legendre, P. (2002), Nonlinear redundancy analysis and canonical correspondence analysis based on polynomial regression, Ecology, 83(4) 1146-1161.

Makarenkov, V. (2001), T-REX: reconstructing and visualizing phylogenetic trees and reticulation networks, Bioinformatics, 17 (7), 664-668.

Makarenkov, V. and Legendre, P. (2001), Optimal Variable Weighting for Ultrametric and Additive Trees and K-means Partitioning: Methods and Software, Journal of Classification, 18, 245-271.

Makarenkov, V. and Leclerc, B. (2000), Comparison of additive trees using circular orders, Journal of Computational Biology, 7, 5, 731-744.

Makarenkov, V. and Legendre, P. (1999), Une methode d'analyse canonique non-lineaire et son application a des donnees biologiques, Mathematique, Informatique et Sciences Humaines, 147, 135-147.

Makarenkov, V. and Leclerc, B. (1999), An algorithm for the fitting of a phylogenetic tree according to a weighted least-squares criterion, Journal of Classification, 16, 1, 3-26.

Leclerc, B. and Makarenkov, V. (1998), On some relations between 2-trees and tree metrics, Discrete Mathematics, 192, 223-251.

Makarenkov, V. and Leclerc, B. (1997), Circular orders of tree metrics, and their uses for the reconstruction and fitting of phylogenetic trees, Mathematical Hierarchies and Biology (B. Mirkin, F.R. McMorris, F. Roberts, A. Rzhetsky, eds.), DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Amer. Math. Soc., Providence, RI, 183-208.


Refereed conference proceedings and book chapters

de Amorim, R.C., Tahiri, N., Mirkin, B. and Makarenkov, V. (2017), A median-based consensus rule for distance exponent selection in the framework of intelligent and weighted Minkowski clustering, Proceedings of IFCS 2015, Data Science - Innovative Developments in Data Analysis and Clustering, Springer Verlag, to appear.

Badescu, D., Tahiri, N. and Makarenkov, V. (2017), A new fast method for detecting and validating horizontal gene transfer events using phylogenetic trees and aggregation functions, Pattern Recognition in Computational Molecular Biology: Techniques and Approaches, 483-504, John Wiley & Sons, Inc.

Daigle, B., Makarenkov, V. and Diallo, A.B. (2015). Effect of Hundreds Sequenced Genomes on the Classification of Human Papilloma Viruses, Proceedings of SFC-GfKL 2013, Data Science, Learning by Latent Structures, and Knowledge Discovery, Springer Verlag, 309-318.

Tahiri, N., Willems, M. and Makarenkov, V. (2015). Inférence des super-arbres multiples en utilisant l'algorithme des k-moyennes. Proceedings of SFC 2015, Nantes (France), 110-114.

Tahiri, N., Willems, M. and Makarenkov, V. (2014). Classification d’arbres phylogenetiques basee sur l’algorithme des k-moyennes, Proceedings of SFC 2014, Rabat, Morocco, 49-54.

Makarenkov, V., Boc, A. and Legendre, P. (2014). A new algorithm for inferring hybridization events based on the detection of horizontal gene transfers, Clusters, Orders, and Trees: Methods and Applications, Springer Verlag New-York, 273-293.

Boc, A., Legendre, P. and Makarenkov, V. (2013). An efficient algorithm for the detection and classification of horizontal gene transfer events and identification of mosaic genes, Proceedings of IFCS 2011, Algorithms from and for Nature and Life, Springer Verlag, 253-260.

Makarenkov, V., Dragiev, P. and Nadon, R. (2013). A new effective method for elimination of systematic error in experimental high-throughput screening, Proceedings of IFCS 2011. Algorithms from and for Nature and Life, Springer Verlag, 269-277.

Szathmary, L., Valtchev, P., Napoli, A., Godin, R., Boc, A. and Makarenkov, V. (2011). Fast Mining of Iceberg Lattices: A Modular Approach Using Generators, Napoli, A. and Vychodil, V. eds, Proceedings of the 8th International Conference on Concept Lattices and their Applications, CLA 2011, Oct. 2011, Nancy, France, 191–206.

Szathmary, L., Boc, A., Valtchev, P. and Makarenkov, V. (2011). Personal assets evolution: a new free of charge web server application for a real-time tracking of personal investments and net worth, Proceedings of the 2011 international conference on e-learning, e-business, enterprise information systems, and e-gouvernment, EEE-2011, July 2011, USA, 260-265.

Boc, A., Diallo, Alpha. B. and Makarenkov, V. (2011). Un nouvel algorithme pour la detection des transferts horizontaux de genes partiels entre les especes et pour la classification des transferts inferes, Proceedings of the 18-emes Rencontres de la SFC, SFC-2011, Orleans, France, 25-28.

Mballo, C. and Makarenkov, V. (2010). Using unsupervised machine learning methods in high-throughput screening. Proceedings of the 2010 International Conference on Data Mining (DMIN'10: July 12-15, Las Vegas, USA), CSREA Press 2010, 392-395.

Mballo, C. and Makarenkov, V. (2010). Assessing the performance of machine learning methods in high-throughput screening. Sixth International Conference on Intelligent Systems: Theory and Applications, Rabat, Morocco, May, 04-05, 2010, 131-138.

Boc, A., Di Sciullo, A-M. and Makarenkov, V. (2010). Classification of the Indo-European languages using a phylogenetic network approach, in Classification as a Tool for Research, Locarek-Junge, H. and Weihs, C. eds, proceedings of IFCS 2009. Studies in Classification, Data Analysis, and Knowledge Organization, Springer Berlin-Heidelberg-New York, 647-655.

Mballo, C. and Makarenkov, V. (2010). Virtual high throughput screening using machine learning methods, in Classification as a Tool for Research, Locarek-Junge, H. and Weihs, C. eds, proceedings of IFCS 2009. Studies in Classification, Data Analysis, and Knowledge Organization, Springer Berlin-Heidelberg-New York, 517-524.

Badescu, D., Diallo, A.B. and Makarenkov, V. (2010). Identification of specific genomic regions responsible for the invasivity of Neisseria Meningitidis, in Classification as a Tool for Research, Locarek-Junge, H. and Weihs, C. eds, proceedings of IFCS 2009. Studies in Classification, Data Analysis, and Knowledge Organization, Springer Berlin-Heidelberg-New York, 491-499.

Makarenkov, V., Dragiev, P., Mballo, C. and Nadon, R. (2009). Polynomial RDA and Machine Learning Approaches for Modeling the Relationships Between HTS Data and Chemical Descriptors, proceedings of SFC-CLADAG 2008, Springer Verlag, 8 pages (to appear).

Diallo, A.B., Badescu, D., Blanchette, M. and Makarenkov, V. (2009), Classification of the Human Papilloma Viruses, proceedings of SFC-CLADAG 2008, Springer Verlag, 8 pages (to appear).

Badescu, D., Diallo, A. B., Blanchette, M. and Makarenkov, V. (2008). An evolution study of the human papillomavirus genomes, to appear in proceedings of RECOMB Comparative Genomics 2008, Springer, Lecture Notes in Bioinformatics Series, Paris, 128-140.

Makarenkov, V., Boc, A., Diallo, Alpha. B. and Diallo Abdoulaye B. (2008), Algorithms for detecting horizontal gene transfers: Theory and practice, in Data Mining and Mathematical Programming, P.M. Pardalos and P. Hansen eds., CRM Proceedings and AMS Lecture Notes, 45, 159-179.

Diallo, A.B., Badescu, D., Makarenkov, V. and Blanchette M. (2008). Phylogeny of the human papilloma viruses and carcinoma classification, Proceedings of the First joint meeting SFC-CLADAG 2008, Caserta, Italy, 285-288.

Dragiev, P., Nadon, R. and Makarenkov, V. (2008). Modeling the relashionships between experimental HTS data and related chemical compounds, Proceedings of the First joint meeting SFC-CLADAG 2008, Caserta, Italy, 289-292.

Makarenkov, V., Boc, A. and Diallo, Alpha. B. (2007). La dissimilarite de bipartition et son utilisation pour detecter les transferts horizontaux de genes, Proceedings of the 14-emes Rencontres de la SFC 2007, ENST de Paris, France, 90-93.

Nguyen, D., Boc, A., Diallo, A. B. and Makarenkov, V. (2007). Etude de la classification des bacteriophages, Proceedings of the 14-emes Rencontres de la SFC 2007, ENST de Paris, France, 161-164.

Diallo, A.B., Makarenkov, V. and Blanchette, M (2006). Finding Maximum Likelihood Indel Scenarios. Proceedings of the 4th RECOMB Comparative Genomics Satellite Workshop. Lecture Notes in Bioinformatics, Springer Verlag, Comparative Genomics, Lecture Notes in Computer Science, 4205, 171-185.

Makarenkov, V., Boc, A., Delwiche, Diallo, A.B., C. F. and Philippe, H. (2006). New efficient algorithm for modeling partial and complete gene transfer scenarios. Data Science and Classification, V. Batagelj, H.-H. Bock, A. Ferligoj, and A. Ziberna (Eds.), IFCS 2006, Series: Studies in Classification, Data Analysis, and Knowledge Organization, Springer Verlag, 341-349.

Diallo, A.B., Makarenkov, V., Blanchette, M. and Lapointe, F.-J. (2006). A new method for assessing missing nucleotides in DNA sequences in the framework of a generic evolutionary model. Data Science and Classification, V. Batagelj, H.-H. Bock, A. Ferligoj, and A. Ziberna (Eds.), IFCS 2006, Series: Studies in Classification, Data Analysis, and Knowledge Organization, Springer Verlag, 333-341.

Gagarin, A., Kevorkov, D. and Makarenkov, V. (2006). Comparison of two methods for detecting and correcting systematic error in high-throughput screening data. Data Science and Classification, V. Batagelj, H.-H. Bock, A. Ferligoj, and A. Ziberna (Eds.), IFCS 2006, Series: Studies in Classification, Data Analysis, and Knowledge Organization, Springer Verlag, 241-249.

D. Kevorkov and V. Makarenkov (2005). Quality control and data correction in high-throughput screening, proceedings of the SFC2005, Montreal, 159-163.

D. Nguyen, A. Boc and V. Makarenkov (2005), HGT-Simulator: logiciel pour simuler des transferts horizontaux de genes, proceedings of the SFC2005, Montreal, 215-219.

A. Diallo, A. Diallo and V. Makarenkov (2005), Une nouvelle methode pour l'estimation de nucleotides manquants, proceedings of the SFC2005, Montreal, 121-125.

V. Makarenkov and A. Boc (2004), Deux modeles de detection de transferts horizontaux de genes dans une classification d'especes, SFC04, Bordeaux, France.

A. B. Diallo, V. Makarenkov, A. Boc and F-J. Lapointe (2004), Une nouvelle methode efficace pour l'estimation des donnees manquantes dans les sequences des nucleotides avant la reconstruction phylogenetique, JOBIM 2004, Montreal, Canada.

A. Boc, V. Makarenkov and A. B. Diallo (2004), Une nouvelle methode pour la detection de transferts horizontaux de gene : la reconciliation topologique d'arbres de gene et d'especes, JOBIM 2004, Montreal, Canada.

Makarenkov, V., Boc, A. and Diallo, A.B. (2004), Determining horizontal gene transfers in species classification: unique scenario, In Classification, Clustering, and Data Mining Applications, IFCS 2004, Springer Verlag, Chicago, 439-446.

Boc, A. and Makarenkov, V. (2003), New Efficient Algorithm for Detection of Horizontal Gene Transfer Events, Lecture Notes in Bioinformatics, G. Benson and R. Page (Eds.), 3rd Workshop on Algorithms in Bioinformatics, Springer, 190-201.

Boc, A., Diallo A.B. and Makarenkov, V. (2003), Comment detecter le transfert lateral de genes dans la classification des especes, Methode et Perspectives en Classification, Y. Dodge and G. Melfi (Eds.), 10-emes Rencontres de la Societe Francophone de Classification, Presses Academiques Neuchatel, 75-78.

Makarenkov, V. and Legendre, P. (2003), Optimal Variable Selection for Ultrametric and Additive Tree Clustering and K-means Partitioning, proceedings of the 2nd International Conference on Control Sciences of the Institute of Control Sciences, RAN, Moscow, Russia, v. 1, 262-72;269.

Makarenkov, V. and Boc, A. (2002), La reconstruction des arbres phylogenetiques et reticulogrammes a l'aide du logiciel T-Rex, Recueil des actes des 9-iemes rencontres de la Societe Francophone de Classification, Toulouse, France.

Makarenkov, V. (2002), Comparison of four methods for inferring phylogenetic trees from incomplete dissimilarity matrices, in Classification, Clustering, and Data Analysis, (K. Jajuga, A. Sokolowski et H.-H. Bock, eds), Springer, Cracow, Poland, 371-378.

Makarenkov, V. (2001), Une nouvelle methode efficace pour la reconstruction des arbres additifs à partir des matrices de distances incomletes. Recueil des actes des 8-iemes rencontres de la Societe Francophone de Classification, Universite de Antilles-Guyane, Pointe-à-Pitre, Guadeloupe, 238-244.

Makarenkov, V., Bazin, E. and Legendre, P. (2001), T-Rex - software for reconstructing phylogenetic trees and reticulation networks. How to remove the phylogeny effect using multiple regression on distance matrices, Currents in Computational Molecular Biology, (N. El-Mabrouk, T. Lengauer, and D. Sankoff, eds.), RECOMB 2001, Montreal, 209-210.

Guenoche, A., Leclerc, B. and Makarenkov, V. (2000), Generalized Trees Related with Tree Metrics, Electronic Notes in Discrete Mathematics, Volume 5, the sixth international conference on the graph theory, Marseille (France), 18 pages.

Makarenkov, V. and Legendre, P. (2000), Improving the additive tree representation of a given dissimilarity matrix using reticulations, Data analysis, Classification and Related Methods (H.A.L. Kiers, J.-P. Rasson, P.J.F. Groenen, M. Schader, eds), Springer, 35-40.

Makarenkov, V. and Legendre, P. (1998), Une methode d'ordination canonique non-lineaire et son application à des donnees ecologiques, Recueil des actes des 6-iemes rencontres de la Societe Francophone de Classification, Agro Montpellier, 147-151.

Leclerc, B. and Makarenkov, V. (1997), Elimination orders for tree metrics,Proceedings of the International Conference on Ordinal et Symbolic Data Analysis, March 19-21, Darmstadt, Technische Hochschule Darmstadt, 1997, 17-21.

Leclerc, B. and Makarenkov, V. (1997), Dissimilarites d'arbres et graphes triangules, Recueil des actes des 5-iemes rencontres de la Societe Francophone de Classification, Lyon, Universite Lyon 2, 311-316.

Makarenkov, V. and Leclerc, B. (1996), Ordres circulaires d'une distance d'arbres, Recueil des actes des 4-iemes rencontres de la Societe Francophone de Classification, Vannes, Universite de Bretagne Sud, 231-232.



Other publications and research reports

Makarenkov, V. and Leclerc, B. (1999), Optimal algorithms for computing the Robinson and Foulds topologic distance between two trees and the strict consensus trees of k trees given their distance matrices, Les cahiers du C.A.M.S., 164, 16 pages, available on the CAMS server.

Makarenkov, V. and Leclerc, B. (1997), On a class of graphs related with tree metrics, Les cahiers du C.A.M.S., 131, 22 pages, available on the CAMS server.

Makarenkov, V. and Leclerc, B. (1997), An algorithm for the fitting of a tree metric according to a weighted least squares criterion, Les cahiers du C.A.M.S., 149, 23 pages, available on the CAMS server.

Makarenkov, V. (1996), Deux algorithmes d'approximation d'une dissimilarite par une distance d'arbre au sens du critere des moindres carres ponderes, Les cahiers du C.A.M.S., 128, 22 pages, available on the CAMS server.

Makarenkov, V. and Leclerc, B. (1996), Tree metrics and their circular orders: some uses for the reconstruction and fitting of phylogenetic trees, Les cahiers du C.A.M.S., 123, 25 pages, available on the CAMS server.

Makarenkov, V. (1994), Ordres de Yushmanov et ordres diagonaux plans pour le codage et la reconstruction des X-arbres values, research report, Universite Paris V, Sorbonne.

Makarenkov, V. (1992), Sur le development d'un modele mathematique en economie, research report, Moscow State University Lomonossov, Moscow, Russia.



Bioinformatics software and user guides

Makarenkov, V and Boc, A. (2012), T-REX (Tree and Reticulogram Reconstruction) web server.

Makarenkov, V., Kevorkov, D. and Zentilli, P. (2006), HTS-Corrector: software for statistical analysis and correction of experimental data.

Makarenkov, V. et al. (2001), Program T-REX (tree and reticulogram reconstruction). Departement de sciences biologiques, Universite de Montreal. User guide for Macintosh of 3 pages and Windows 9x/NT (GUI) of 60 pages.

Makarenkov, V. and Legendre, P. (1999), Program OVW (optimal variable weighting for ultrametric and additive clustering and k-means partitioning). Departement de sciences biologiques, Universite de Montreal. User guide for Windows 9x/NT, Macintosh and UNIX versions, 5 pages.

Makarenkov, V. and Legendre, P. (1999), Linear and Polynomial RDA and CCA (linear and polynomial canonical analysis). Departement de sciences biologiques, Universite de Montreal. User guide for Windows 9x/NT, and Macintosh versions, 9 pages.

Makarenkov, V. (1998), Program for computation of the Robinson and Foulds topological distance between two phylogenetic trees. Departement de sciences biologiques, Universite de Montreal. User guide for Windows 9x/NT, Macintosh and UNIX versions, 4 pages.


Ph. D. thesis

Makarenkov, V. (1997), Combinatorial properties of phylogenetic trees and tree metrics. Algorithms and applications, Ph. D. thesis, Institute of Control Sciences (Moscow, Russia) and EHESS (Paris, France).

Ph. D. Thesis Summary
My thesis was devoted to the combinatorial study of phylogenetic trees and tree metrics, and to the algorithmic uses of the obtained properties. Phylogenetic (i.e., additive) trees were first characterized in Russia by Zaretskii (1965), and later generalized by Buneman (1971). The interest in their study grew considerably in the eighties, when the diversity of their domains of application was perceived. They have been used, for instance, in coding theory, in cognitive psychology (as models for subjective distances), in archaeology (for the relation of manuscripts), in linguistics (for distances between natural languages) and, more generally, in all situations where a bifurcation model can be postulated or used. Currently, most of the contributions to these metrics are motivated by their role in phylogenetics, where they represent an intuitive model for molecular distances. An important part of the literature on this subject is devoted to the methods (algorithms and programs) for the fitting of a tree metric to an observed distance (dissimilarity) matrix. Problems of this type are generally NP-hard and the methods are heuristic. The original contributions of this thesis were three-fold. New combinatorial properties of tree metrics were obtained. These properties were used for the design of optimal and original algorithms for the recognition and the fitting of tree metrics. These algorithms were implemented in C++ programming language (for Windows 95, MS-DOS and UNIX platforms) and combined with several programs of optimization and statistical data generation into a program library. Numerous tests of the introduced algorithms on real and artificial data have demonstrated their advantage relative to some of the most popular traditional methods dealing with tree structures.


Presentations 1996-2001




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