Matthieu Vignes

438 total citations
33 papers, 245 citations indexed

About

Matthieu Vignes is a scholar working on Molecular Biology, Plant Science and Animal Science and Zoology. According to data from OpenAlex, Matthieu Vignes has authored 33 papers receiving a total of 245 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Plant Science and 4 papers in Animal Science and Zoology. Recurrent topics in Matthieu Vignes's work include Bioinformatics and Genomic Networks (10 papers), Gene expression and cancer classification (8 papers) and Gene Regulatory Network Analysis (5 papers). Matthieu Vignes is often cited by papers focused on Bioinformatics and Genomic Networks (10 papers), Gene expression and cancer classification (8 papers) and Gene Regulatory Network Analysis (5 papers). Matthieu Vignes collaborates with scholars based in New Zealand, France and United Kingdom. Matthieu Vignes's co-authors include Lionel Dupuy, Florence Forbes, Philip J. White, Thomas Schiex, Blair M. McKenzie, Christine Cierco-Ayrolles, Simon de Givry, David Allouche, N. López‐Villalobos and Jimmy Vandel and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Matthieu Vignes

31 papers receiving 238 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matthieu Vignes New Zealand 9 98 49 30 22 20 33 245
Zhiyu Chen China 6 36 0.4× 85 1.7× 20 0.7× 21 1.0× 16 0.8× 9 301
Xiao Cheng China 12 65 0.7× 79 1.6× 7 0.2× 19 0.9× 12 0.6× 35 369
Luke Sheneman United States 4 204 2.1× 30 0.6× 16 0.5× 6 0.3× 37 1.9× 11 315
A. Aly Egypt 9 21 0.2× 136 2.8× 16 0.5× 24 1.1× 6 0.3× 51 222
Jonathon Romero United States 9 75 0.8× 123 2.5× 29 1.0× 11 0.5× 55 2.8× 10 382
Chufeng Wang China 13 41 0.4× 120 2.4× 12 0.4× 16 0.7× 29 1.4× 28 401
Xin‐Yi Chua Australia 5 152 1.6× 18 0.4× 14 0.5× 15 0.7× 23 1.1× 13 224
Afrânio Márcio Corrêa Vieira Brazil 9 47 0.5× 43 0.9× 28 0.9× 33 1.5× 110 5.5× 32 412
Gavin J. S. Ross United Kingdom 5 55 0.6× 136 2.8× 4 0.1× 12 0.5× 31 1.6× 10 285
Steven T. Callen United States 7 62 0.6× 278 5.7× 9 0.3× 13 0.6× 52 2.6× 7 412

Countries citing papers authored by Matthieu Vignes

Since Specialization
Citations

This map shows the geographic impact of Matthieu Vignes's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthieu Vignes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthieu Vignes more than expected).

Fields of papers citing papers by Matthieu Vignes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthieu Vignes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthieu Vignes. The network helps show where Matthieu Vignes may publish in the future.

Co-authorship network of co-authors of Matthieu Vignes

This figure shows the co-authorship network connecting the top 25 collaborators of Matthieu Vignes. A scholar is included among the top collaborators of Matthieu Vignes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthieu Vignes. Matthieu Vignes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hirst, David, et al.. (2025). MOTL: enhancing multi-omics matrix factorization with transfer learning. Genome biology. 26(1). 224–224.
2.
Shepherd, Daniel, et al.. (2025). Factors predicting parenting stress in the autism spectrum disorder context: A network analysis approach. PLoS ONE. 20(4). e0319036–e0319036. 1 indexed citations
3.
Vignes, Matthieu, et al.. (2025). Evaluation of protein intake and protein quality in New Zealand vegans. PLoS ONE. 20(4). e0314889–e0314889. 2 indexed citations
4.
Vignes, Matthieu, Keren E. Dittmer, Mark R. Waterland, et al.. (2024). Infrared Spectroscopy of Synovial Fluid Shows Accuracy as an Early Biomarker in an Equine Model of Traumatic Osteoarthritis. Animals. 14(7). 986–986. 1 indexed citations
5.
Wang, Yu, Émilie Vallée, Christopher Compton, et al.. (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. 106115–106115. 5 indexed citations
6.
Shepherd, Daniel, et al.. (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. 104808–104808. 3 indexed citations
7.
Narayanan, Ajit, et al.. (2024). Centrality statistics of symptom networks of schizophrenia: a systematic review. Psychological Medicine. 54(6). 1061–1073. 6 indexed citations
8.
Dittmer, Keren E., Matthieu Vignes, Kristene Gedye, et al.. (2023). Plasma and Synovial Fluid Cell-Free DNA Concentrations Following Induction of Osteoarthritis in Horses. Animals. 13(6). 1053–1053. 4 indexed citations
9.
10.
Thomson, Susan, Matthieu Vignes, Patrick J. Biggs, et al.. (2023). Investigating the genetic components of tuber bruising in a breeding population of tetraploid potatoes. BMC Plant Biology. 23(1). 238–238. 4 indexed citations
11.
Boulic, Mikael, et al.. (2023). Validation of low-cost air quality monitoring platforms using model-based control charts. Journal of Building Engineering. 82. 108357–108357. 4 indexed citations
12.
Ezanno, Pauline, Sébastien Picault, Gaël Beaunée, et al.. (2022). The African swine fever modelling challenge: Model comparison and lessons learnt. Epidemics. 40. 100615–100615. 11 indexed citations
13.
López‐Villalobos, N., et al.. (2021). Identifying Health Status in Grazing Dairy Cows from Milk Mid-Infrared Spectroscopy by Using Machine Learning Methods. Animals. 11(8). 2154–2154. 22 indexed citations
14.
Mezura‐Montes, Efrén, Matthieu Vignes, Morgane Térézol, et al.. (2021). A multi-objective genetic algorithm to find active modules in multiplex biological networks. PLoS Computational Biology. 17(8). e1009263–e1009263. 14 indexed citations
15.
Picheny, Victor, et al.. (2017). Correction to: Inferring large graphs using $$\ell _{1}$$ ℓ 1 -penalized likelihood. Statistics and Computing. 28(6). 1231–1231. 1 indexed citations
16.
Picheny, Victor, et al.. (2017). Inferring large graphs using $$\ell _1$$ ℓ 1 -penalized likelihood. Statistics and Computing. 28(4). 905–921. 1 indexed citations
17.
Cierco-Ayrolles, Christine, et al.. (2014). Sparse regression and support recovery withL2-Boosting algorithms. Journal of Statistical Planning and Inference. 155. 19–41. 3 indexed citations
18.
Vignes, Matthieu, Jimmy Vandel, David Allouche, et al.. (2011). Gene Regulatory Network Reconstruction Using Bayesian Networks, the Dantzig Selector, the Lasso and Their Meta-Analysis. PLoS ONE. 6(12). e29165–e29165. 59 indexed citations
19.
Vignes, Matthieu & Florence Forbes. (2009). Gene Clustering via Integrated Markov Models Combining Individual and Pairwise Features. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 6(2). 260–270. 17 indexed citations
20.
Dupuy, Lionel, Matthieu Vignes, Blair M. McKenzie, & Philip J. White. (2009). The dynamics of root meristem distribution in the soil. Plant Cell & Environment. 33(3). 358–369. 30 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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