淘料视频

Dr Matthieu Vignes staff profile picture

Contact details +6469517654

Dr Matthieu Vignes DEA, PhD

Senior Lecturer in Statistics

Doctoral Supervisor
School of Mathematical and Computational Sciences

Matthieu studied Applied Maths/Stats at the ENS Lyon (France) before doing his PhD in Grenoble (2007, INRIA Rhone-Alpes, France). He then joined BioSS in Dundee and Aberdeen (Scotland) from 2006 to 2009 as a Statistician. He then became a Research Fellow in the Maths and Comput. Sc. dpt of the INRAE-Toulouse (France) in 2009 (present: detached position).

Matthieu is now a Senior Lecturer in Statistical Genetics at 淘料视频 (New Zealand).

Matthieu's work focuses on deciphering relationships between entities in a complex (e.g. biological) system; please have a look at his research interests.

Professional

Contact details

  • Ph: +64(0)6 951 7654 (direct) or +64(0)6 356 9099; ext. 84654
    Location: B3.06, Science Tower B
    Campus: Turitea

Qualifications

  • Dipl么me d'脡tudes approfondies en math茅matiques - Universit茅 Claude Bernard Lyon 1 (2002)
  • Doctor of Philosophy - Joseph Fourier University (2007)

Certifications and Registrations

  • Licence, Supervisor, 淘料视频

Research Expertise

Research Interests

My research is motivated by the understanding of the structure(s) which govern(s) the behaviour of complex systems. Mostly, I have been working with high-throughput data generated by biological organims, regarded as layers of components of different natures which interact with each other possibly fulfilling different goals.
To this end, I am interested in probabilistic graphical modelling as a convenient way of representing the system under study and how its constituting elements interact. I am often faced with high-dimensional data posing both statistical and computational challenges. Missingness in the data sets at hand can also be a hindrance. Data sets are heterogeneous (e.g. mixing discrete and continuous data), sampling is certainly not independent and identically distributed and off-equilibrium and measurements noisy.
Recently, I am moving towards a causal interpretation of learnt relationships, hopefully revealing realistic mechanisms which explain the inner functioning of the system.
I have also been involved in the study of epidemiological models at different scales.

Thematics

Future Food Systems

Area of Expertise

Field of research codes
Applied Mathematics (010200): Applied Statistics (010401):
Artificial Intelligence and Image Processing (080100):
Biological Mathematics (010202): Biostatistics (010402):
Information And Computing Sciences (080000):
Mathematical Sciences (010000): Numerical and Computational Mathematics (010300): Optimisation (010303):
Pattern Recognition and Data Mining (080109):
Statistical Theory (010405): Statistics (010400): Stochastic Analysis and Modelling (010406)

Keywords

  • Probabilistic graphical models (Bayesian networks, GGM...)
  • High-dimensional (biological) data
  • Gene network inference
  • Causality
  • Data integration
  • Computational statistics

Research Outputs

Journal

Angelin-Bonnet, O., Vignes, M., Biggs, PJ., Baldwin, S., & Thomson, S. (2024). Visual Integration of Genome-Wide Association Studies and Differential Expression Results with the Hidecan R Package.. Genes (Basel). 15(10)
[Journal article]Authored by: Biggs, P., Vignes, M.
Kashnitsky, Y., Roberge, G., Mu, J., Kang, K., Wang, W., Vanderfeesten, M., . . . Labrosse, I. (2024). Evaluating approaches to identifying research supporting the United Nations Sustainable Development Goals. Quantitative Science Studies. 5(2), 408-425
[Journal article]Authored by: Vignes, M.
Shepherd, D., Buchwald, K., Siegert, RJ., & Vignes, M. (2024). Using network analysis to identify factors influencing the heath-related quality of life of parents caring for an autistic child. Research in Developmental Disabilities. 152
[Journal article]Authored by: Vignes, M.
Panizzi, L., Vignes, M., Dittmer, KE., Waterland, MR., Rogers, CW., Sano, H., . . . Riley, CB. (2024). Infrared Spectroscopy of Synovial Fluid Shows Accuracy as an Early Biomarker in an Equine Model of Traumatic Osteoarthritis. Animals. 14(7)
[Journal article]Authored by: Dittmer, K., Panizzi, L., Rogers, C., Vignes, M., Waterland, M.
Wang, Y., Vallée, E., Compton, C., Heuer, C., Guo, A., Wang, Y., . . . Vignes, M. (2024). A novel Bayesian Latent Class Model (BLCM) evaluates multiple continuous and binary tests: A case study for Brucella abortus in dairy cattle. Preventive Veterinary Medicine. 224
[Journal article]Authored by: Compton, C., Vallee, E., Vignes, M.
Buchwald, K., Narayanan, A., Siegert, RJ., Vignes, M., Arrowsmith, K., & Sandham, M. (2024). Centrality statistics of symptom networks of schizophrenia: A systematic review. Psychological Medicine. 54(6), 1061-1073
[Journal article]Authored by: Vignes, M.
Boulic, M., Phipps, R., Wang, Y., Vignes, M., & Adegoke, NA. (2024). Validation of low-cost air quality monitoring platforms using model-based control charts. Journal of Building Engineering. 82
[Journal article]Authored by: Boulic, M., Vignes, M.
Angelin-Bonnet, O., Thomson, S., Vignes, M., Biggs, PJ., Monaghan, K., Bloomer, R., . . . Baldwin, S. (2023). Investigating the genetic components of tuber bruising in a breeding population of tetraploid potatoes. BMC Plant Biology. 23(1)
[Journal article]Authored by: Biggs, P., Vignes, M.
Marquetoux, N., Vignes, M., Burroughs, A., Sumner, E., Sawford, K., & Jones, G. (2023). Evaluation of the accuracy of the IDvet serological test for Mycoplasma bovis infection in cattle using latent class analysis of paired serum ELISA and quantitative real-time PCR on tonsillar swabs sampled at slaughter. PLoS ONE. 18(5 MAY)
[Journal article]Authored by: Vignes, M.
Panizzi, L., Dittmer, KE., Vignes, M., Doucet, JS., Gedye, K., Waterland, MR., . . . Riley, CB. (2023). Plasma and Synovial Fluid Cell-Free DNA Concentrations Following Induction of Osteoarthritis in Horses. Animals. 13(6)
[Journal article]Authored by: Dittmer, K., Panizzi, L., Rogers, C., Vignes, M., Waterland, M.
Panizzi, L., Vignes, M., Dittmer, KE., Waterland, MR., Rogers, CW., Sano, H., . . . Riley, CB. (2022). Infrared spectroscopy of serum fails to identify early biomarker changes in an equine model of traumatic osteoarthritis. Osteoarthritis and Cartilage Open. 4(4)
[Journal article]Authored by: Dittmer, K., Panizzi, L., Rogers, C., Vignes, M., Waterland, M.
Ezanno, P., Picault, S., Bareille, S., Beaunée, G., Boender, GJ., Dankwa, EA., . . . Vergne, T. (2022). The African swine fever modelling challenge: Model comparison and lessons learnt. Epidemics. 40
[Journal article]Authored by: Vignes, M.
Lawrence, KE., Flay, KJ., Munday, JS., Aberdein, D., Thomson, NA., Vignes, M., . . . Ridler, AL. (2022). Longitudinal study of the effect of sporidesmin toxicity on lamb production and serum biochemistry in a flock of 46 Romney ewes using a standardised measure of liver damage. New Zealand Veterinary Journal. 70(4), 198-210
[Journal article]Authored by: Aberdein, D., Lawrence, K., Munday, J., Ridler, A., Thomson, N., Vignes, M.
Novoa-Del-Toro, EM., Mezura-Montes, E., Vignes, M., Térézol, M., Magdinier, F., Tichit, L., . . . Baudot, A. (2021). A multi-objective genetic algorithm to find active modules in multiplex biological networks. PLoS Computational Biology. 17(8)
[Journal article]Authored by: Vignes, M.
Hernández, BC., Lopez-Villalobos, N., & Vignes, M. (2021). Identifying health status in grazing dairy cows from milk mid-infrared spectroscopy by using machine learning methods. Animals. 11(8)
[Journal article]Authored by: Lopez-Villalobos, N., Vignes, M.
Angelin-Bonnet, O., Biggs, PJ., Baldwin, S., Thomson, S., & Vignes, M. (2020). Sismonr: Simulation of in silico multi-omic networks with adjustable ploidy and post-transcriptional regulation in R. Bioinformatics. 36(9), 2938-2940
[Journal article]Authored by: Biggs, P., Vignes, M.
Peyrard, N., Cros, MJ., de Givry, S., Franc, A., Robin, S., Sabbadin, R., . . . Vignes, M. (2019). Exact or approximate inference in graphical models: why the choice is dictated by the treewidth, and how variable elimination can be exploited. Australian and New Zealand Journal of Statistics. 61(2), 89-133
[Journal article]Authored by: Vignes, M.
Parry, K., & Vignes, M. (2019). Introduction to High-Dimensional Statistics. Biometrics. 74(4), 1524-1525 Retrieved from https://onlinelibrary.wiley.com/doi/10.1111/biom.12979
[Journal article]Authored by: Vignes, M.
Ghose, A., Pizzol, M., McLaren, SJ., Vignes, M., & Dowdell, D. (2019). Refurbishment of office buildings in New Zealand: identifying priorities for reducing environmental impacts. International Journal of Life Cycle Assessment. 24(8), 1480-1495
[Journal article]Authored by: McLaren, S., Vignes, M.
Champion, M., Picheny, V., & Vignes, M. (2018). Correction to: Inferring large graphs using 鈩<inf>1</inf> -penalized likelihood (Statistics and Computing, (2018), 28, 4, (905-921), 10.1007/s11222-017-9769-z). Statistics and Computing. 28(6), 1231
[Journal article]Authored by: Vignes, M.
Champion, M., Picheny, V., & Vignes, M. (2018). Inferring large graphs using 鈩<inf>1</inf> -penalized likelihood. Statistics and Computing. 28(4), 905-921
[Journal article]Authored by: Vignes, M.
Vignes, MCL., Sammarro, M., Schfefheere, A., White, A., & Marsland, S. (2017). Bayesian Networks: With Examples in R. Australian & New Zealand Journal of Statistics.
[Book Review]Authored by: Vignes, M.
Vignes, MCL. (2017). Book Review: Modern optimization with R (by P. Cortez). Australian & New Zealand Journal of Statistics. 59(2), 235-236
[Book Review]Authored by: Vignes, M.
Vignes, MCL. (2016). Book Review: Inference principles for biostatisticians by Ian C. Marschner. Australian and New Zealand Journal of Statistics. 57(4), 571-572
[Book Review]Authored by: Vignes, M.
Villa-Vialaneix, N., Vignes, M., Viguerie, N., & Cristobal, MS. (2014). Inferring networks from multiple samples with consensus LASSO. Quality Technology and Quantitative Management. 11(1), 39-60
[Journal article]Authored by: Vignes, M.
Marchand, G., Huynh-Thu, VA., Kane, NC., Arribat, S., Varès, D., Rengel, D., . . . Langlade, NB. (2014). Bridging physiological and evolutionary time-scales in a gene regulatory network. New Phytologist. 203(2), 685-696
[Journal article]Authored by: Vignes, M.
Champion, M., Cierco-Ayrolles, C., Gadat, S., & Vignes, M. (2014). Sparse regression and support recovery with L2-Boosting algorithms. Journal of Statistical Planning and Inference. 155, 19-41
[Journal article]Authored by: Vignes, M.
Vandel, J., Mangin, B., Vignes, M., Leroux, D., Loudet, O., Martin-Magniette, ML., . . . De Givry, S. (2012). Gene regulatory network inference with extended scores for Bayesian networks. Revue d'Intelligence Artificielle. 26(6), 679-708
[Journal article]Authored by: Vignes, M.
Dupuy, LX., & Vignes, M. (2012). An algorithm for the simulation of the growth of root systems on deformable domains. Journal of Theoretical Biology. 310, 164-174
[Journal article]Authored by: Vignes, M.
Vignes, M., Blanchet, J., Leroux, D., & Forbes, F. (2011). SpaCEM<sup>3</sup>: A software for biological module detection when data is incomplete, high dimensional and dependent. Bioinformatics. 27(6), 881-882
[Journal article]Authored by: Vignes, M.
Vignes, M., Vandel, J., Allouche, D., Ramadan-Alban, N., Cierco-Ayrolles, C., Schiex, T., . . . de Givry, S. (2011). Gene regulatory network reconstruction using bayesian networks, the dantzig selector, the lasso and their meta-analysis. PLoS ONE. 6(12)
[Journal article]Authored by: Vignes, M.
Dupuy, L., Vignes, M., Mckenzie, BM., & White, PJ. (2010). The dynamics of root meristem distribution in the soil. Plant, Cell and Environment. 33(3), 358-369
[Journal article]Authored by: Vignes, M.
Dupuy, L., White, PJ., McKenzie, B., & Vignes, M. (2009). Meristematic fronts: A new model of the plant architectural development?. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY A-MOLECULAR & INTEGRATIVE PHYSIOLOGY. 153A(2), S219-S219
[Journal article]Authored by: Vignes, M.
Blanchet, J., & Vignes, M. (2009). A model-based approach to gene clustering with missing observation reconstruction in a Markov random field framework. Journal of Computational Biology. 16(3), 475-486
[Journal article]Authored by: Vignes, M.
Vignes, M., & Forbes, F. (2009). Gene clustering via integrated markov models combining individual and pairwise features. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 6(2), 260-270
[Journal article]Authored by: Vignes, M.

Book

White, A., & Vignes, M. (2019). Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical 淘料视频 in Small Networks. In Methods in Molecular Biology. (pp. 111 - 142).
[Chapter]Authored by: Vignes, M.
Angelin-Bonnet, O., Biggs, PJ., & Vignes, M. (2019). Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling. In Methods in Molecular Biology. (pp. 347 - 383).
[Chapter]Authored by: Biggs, P., Vignes, M.
Allouche, D., Cierco-Ayrolles, C., Givry, SD., Guillermin, G., Mangin, B., Schiex, T., . . . Vignes, M. (2013). A panel of learning methods for the reconstruction of gene regulatory networks in a systems genetics context. In Gene Network Inference: Verification of Methods for Systems Genetics Data. (pp. 9 - 31).
[Chapter]Authored by: Vignes, M.

Thesis

Vignes, M. (2007). Modèles markoviens graphiques pour la fusion de données individuelles et d'interactions : application à la classification de gènes. (Doctoral Thesis, Université Joseph Fourier - Grenoble 1, France)
[Doctoral Thesis]Authored by: Vignes, M.

Report

Champion, M., Picheny, V., & Vignes, M.Inferring large graphs with an l1-penalized likelihood formulation and a hybrid genetic algorithm.
[Technical Report]Authored by: Vignes, M.
Peyrard, N., Givry, SD., Franc, A., Robin, S., Sabbadin, R., Schiex, T., . . . Vignes, M.Exact and approximate inference in graphical models: variable elimination and beyond.
[Technical Report]Authored by: Vignes, M.

Conference

Wang, Y., Vignes, M., Valee, E., Heuer, C., & Compton, C. (2023). Bayesian evaluation of four serological tests for the diagnosis of Brucella abortus in dairy cows. In Conference Proceedings of the Epidemiology, Food Safety, Animal Welfare and Biosecurity Branch of the NZVA Vol. 376 (pp. 23 - 26). , Conference of the Epidemiology, Food Safety, Animal Welfare and Biosecurity Branch of the NZVA
[Conference Abstract]Authored by: Compton, C., Vignes, M.Contributed to by: Compton, C.
Angelin-Bonnet, O., Biggs, PJ., & Vignes, M.The sismonr Package: Simulation of in Silico Multi-Omic Networks in R. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. (pp. 2729 - 2731).
[Conference]Authored by: Biggs, P., Vignes, M.
Schrefheere, A., Campbell, M., Tate, J., Cox, M., & Vignes, MCL.Statistical modelling of expression patterns in hybrid species. Paper presented at the meeting of JOURNÉES OUVERTES DE BIOLOGIE INFORMATIQUE & MATHÉMATIQUES. Lyon, France
[Conference Paper]Authored by: Tate, J., Vignes, M.
Sammarro, M., Friedrich, A., Marshall, J., Biggs, P., French, N., & Vignes, MCL.Revealing the genetic basis for host-pathogen interaction using machine learning. Paper presented at the meeting of JOURNÉES OUVERTES DE BIOLOGIE INFORMATIQUE & MATHÉMATIQUES. Lyon, France
[Conference Paper]Authored by: Biggs, P., French, N., Marshall, J., Vignes, M.
Vignes, MCL. (2016, November). Disease module detection (via graph clustering). Presented at 2016 Joint NZSA+ORSNZ Conference. Auckland, New Zealand.
[Conference Oral Presentation]Authored by: Vignes, M.
Sammarro, M., Schrefheere, A., Biggs, P., marshall, J., Tate, J., Cox, M., . . . Vignes, MCL. (2016). Challenges and leads for modelling complex molecular biological systems. Poster session presented at the meeting of Complex Networks and Applications 2016 workshop. Marseilles, France
[Conference Poster]Authored by: Biggs, P., French, N., Marshall, J., Tate, J., Vignes, M.
Champion, M., Picheny, V., & Vignes, M. (2014, November). Statistical causal inference in a complex system - an hybrid convex-genetic algorithm. Presented at NZSA conference. Wellington, NZ.
[Conference Oral Presentation]Authored by: Vignes, M.
Picheny, V., Vandel, J., Vignes, M., & Villa-Vialaneix, N. (2014). Reconstruction quality of a biological network when its constituting elements are partially observed. Poster session presented at the meeting of AISTAT 2014. Reykjavik, Iceland
[Conference Poster]Authored by: Vignes, M.
Champion, M., Gadat, S., Cierco-Ayrolles, C., & Vignes, MCL.Sparse multivariate regression with L2 -Boosting algorithm.
[Conference Paper]Authored by: Vignes, M.
Allouche, D., CIerco-Ayrolles, C., de Givry, S., Guillermin, G., Mangin, B., Schiex, T., . . . Vignes, M. (2013, March). A panel of learning methods for the reconstruction of gene regulatory networks in a systems genetics context. Presented at StatSeq workshop
[Conference Oral Presentation]Authored by: Vignes, M.
Marchand, G., Huynh-Thu, VA., Kane, N., Arribat, S., Vares, D., Rengel, D., . . . Langlade, .Bridging physiological and evolutionary time scales in a gene regulatory network.
[Conference Paper]Authored by: Vignes, M.
Vandel, J., de Givry, S., Leroux, D., Vignes, MCL., Loudet, O., Martin-Magniette, ML., . . . Mangin, B. (2012, April). Towards Arabidopsis thaliana genetic regulatory network using discrete Bayesian network. Presented at Statseq workshop
[Conference Oral Presentation]Authored by: Vignes, M.
Denoyes, B., Petit, A., Schwab, W., Vignes, M., Munoz-Blanco, J., Lerceteau-Kohler, E., . . . Rothan, C. (2012, February). Genetic dissection of fruit quality traits In the octoploid cultivated strawberry. Presented at VII International strawberry symposium. Beijing, China.
[Conference Oral Presentation]Authored by: Vignes, M.
Fouche, M., Denoyes, B., Rothan, C., Vignes, M., Mangin, B., Petit, A., . . . Villatoro, C. (2012). The role of MYB factor in fruit strawberry color. Poster session presented at the meeting of Sixth Rosaceous Genomics Conference. Mezzocorona, Italy
[Conference Poster]Authored by: Vignes, M.
Dupuy, L., & Vignes, M. (2009). Simplified root architectural models using continuous deformable domains. Plant Growth Modeling, Simulation, Visualization and Applications, Proceedings - PMA09. (pp. 142 - 148).
[Conference Paper in Published Proceedings]Authored by: Vignes, M.
Blanchet, J., & Vignes, M. (2007). Combined expression data with missing values and gene interaction network analysis: A Markovian integrated approach. Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE. (pp. 366 - 373).
[Conference Paper in Published Proceedings]Authored by: Vignes, M.

Other

Champion, M., Picheny, V., & Vignes, M. (2017). GADAG: A genetic algorithm for learning directed acyclic graphs.
[Other]Contributed to by: Vignes, M.

Uncategorised

Angelin-Bonnet, O., Vignes, M., Biggs, P., Baldwin, S., & Thomson, S.April
[Preprint]Authored by: Biggs, P., Vignes, M.

Consultancy and Languages

Languages

  • English
    Last used: today
    Spoken ability: Excellent
    Written ability: Excellent
  • French
    Last used: today
    Spoken ability: Excellent
    Written ability: Excellent
  • German
    Last used: few years ago
    Spoken ability: Average
    Written ability: Average
  • Spanish
    Last used: Today
    Spoken ability: Needs work
    Written ability: Needs work

Teaching and Supervision

Teaching Statement

Papers taught: (at Massey)

  • 161.200 Statistical Modelling (with Martin Hazelton)
  • 161.331 Biostatistics (with Geoff Jones)
  • 161.704 Bayesian statistics (with Mark Bebbington)
  • 161.705 Statistical Inference (with Mark Bebbington)
  • 161.729 Topics in Applied Statistics (with Chris Jewell)
  • 161.744 Statistical Genetics (with Patrick Biggs)

Old teaching:

  • Statistics and learning at SupAero (with Emmanuel Rachelson) and Probability (with Jeremie Bigot) at ISAE SupAero, Toulouse, France, 2012-2014.
  • Statistics: basics to advanced subjects to undergraduates in Biology or Economics (2002-2006), to PhD students and scientists from research institutes (2007-2008).
  • General mathematics: Algebra and Analysis to undergraduates in Mathematics and Physics (2003-2005).
  • General science courses to high-school pupils (2005-2006).

Student supervision:

  • Co-supervision of Luca Panizzi
  • Co-supervision of Thilini Warusawithana
  • Co-supervision of Olivia Angelin-Bonnet (2017-2021, 淘料视频), "Investigation of genotype and phenotype interactions using computational statistics"
  • Co-supervision of Magali Champion PhD (2011-2014, Universite Paul Sabatier Toulouse 3), "Contribution to the modelling and inference of gene regulatory networks"

Graduate Supervision Statement

Please have a look at my research interest, and feel free to contact me, if you would like to do a project with us on the study of data generated from a complex system to decipher its structure. Note that projects range from quite applied to quite theoretical.


Dr Matthieu Vignes is available for Masters and Doctorial supervision.

Summary of Doctoral Supervision

Position Current Completed
Main Supervisor 4 1
Co-supervisor 1 2

Current Doctoral Supervision

Main Supervisor of:

  • James Bristow - Doctor of Philosophy
    Advancing epidemiological insights of New Zealand under climate change using Bayesian spatiotemporal methods
  • Doris Benig - Doctor of Philosophy
    Predictive Genomic Models for Enhancing Taro Agronomic Traits and Environmental Adaptability in Papua New Guinea
  • Mario Prado Lara - Doctor of Philosophy
    An evaluation of statistical classification tools for microbiome and multiomic data
  • Padmini Parthasarathy - Doctor of Philosophy
    Unravelling the Hidden Mysteries of Facial Eczema in Sheep

Co-supervisor of:

  • Patricia Soh - Doctor of Philosophy
    Protein intake and protein quality in vegan diets

Completed Doctoral Supervision

Main Supervisor of:

  • 2021 - Olivia Angelin-Bonnet - Doctor of Philosophy
    Investigation of genotype and phenotype interactions using computational statistics

Co-supervisor of:

  • 2024 - Thilini Warusawithana - Doctor of Philosophy
    Gene duplication fate in a genetic pathway context: An examination of the trichome initiation pathway in the allopolyploid genus Pachycladon (Brassicaceae)
  • 2024 - Luca Panizzi - Doctor of Philosophy
    Biomarker profiling of biologic fluids and tissues from horses with induced carpal osteoarthritis

Media and Links

Other Links