Anaı̈s Baudot

2.8k total citations
54 papers, 1.6k citations indexed

About

Anaı̈s Baudot is a scholar working on Molecular Biology, Genetics and Statistical and Nonlinear Physics. According to data from OpenAlex, Anaı̈s Baudot has authored 54 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 9 papers in Genetics and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Anaı̈s Baudot's work include Bioinformatics and Genomic Networks (25 papers), Gene expression and cancer classification (9 papers) and Complex Network Analysis Techniques (7 papers). Anaı̈s Baudot is often cited by papers focused on Bioinformatics and Genomic Networks (25 papers), Gene expression and cancer classification (9 papers) and Complex Network Analysis Techniques (7 papers). Anaı̈s Baudot collaborates with scholars based in France, Spain and United States. Anaı̈s Baudot's co-authors include Alfonso Valencia, Natalio Krasnogor, Enrico Glaab, Élisabeth Rémy, Rafael Tabarés‐Seisdedos, Reinhard Schneider, Kristina Ibáñez, Christine Brun, Laurent Tichit and César Boullosa and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Anaı̈s Baudot

46 papers receiving 1.6k citations

Peers

Anaı̈s Baudot

CTM

GENET

PRM

Esti Yeger‐Lotem Israel

Martijn van Iersel Netherlands

Aziz M. Mezlini United States

Gürkan Bebek United States

Zhidong Tu United States

Luana Licata Italy

Genie Leung Canada

Max Kotlyar Canada

Martina Kutmon Netherlands

Emek Demir United States

Esti Yeger‐Lotem Israel

Anaı̈s Baudot

1.6k ×1.4

162 ×0.8

CTM

270 ×1.5

GENET

157 ×0.9

46 ×0.3

PRM

Citations per year, relative to Anaı̈s Baudot Anaı̈s Baudot (= 1×) peers Esti Yeger‐Lotem

Countries citing papers authored by Anaı̈s Baudot

Since Specialization

Citations

This map shows the geographic impact of Anaı̈s Baudot'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 Anaı̈s Baudot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anaı̈s Baudot more than expected).

Fields of papers citing papers by Anaı̈s Baudot

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anaı̈s Baudot. 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 Anaı̈s Baudot. The network helps show where Anaı̈s Baudot may publish in the future.

Co-authorship network of co-authors of Anaı̈s Baudot

This figure shows the co-authorship network connecting the top 25 collaborators of Anaı̈s Baudot. A scholar is included among the top collaborators of Anaı̈s Baudot 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 Anaı̈s Baudot. Anaı̈s Baudot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Hirst, David, et al.. (2025). MOTL: enhancing multi-omics matrix factorization with transfer learning. Genome biology. 26(1). 224–224.

Macchi, M., Anaı̈s Baudot, Frada Burstein, et al.. (2025). Recommendations for Successful Development and Implementation of Digital Health Technology Tools. Journal of Medical Internet Research. 27. e56747–e56747. 1 indexed citations

Johari, Mridul, Ozan Özışık, Peter A.C. ’t Hoen, et al.. (2025). Multi-omics analysis in inclusion body myositis identifies mir-16 responsible for HLA overexpression. Orphanet Journal of Rare Diseases. 20(1). 27–27. 1 indexed citations

Bono, Christopher De, Yichi Xu, Camille Humbert, et al.. (2025). Multi-modal refinement of the human heart atlas during the first gestational trimester. Development. 152(5). 2 indexed citations

Conrad, Donald F., et al.. (2025). Benchmark of computational methods to detect digenism in sequencing data. European Journal of Human Genetics. 33(7). 831–841.

Baudot, Anaı̈s, et al.. (2024). Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond. BMC Bioinformatics. 25(1). 70–70. 4 indexed citations

Karnebeek, Clara D.M. van, Anne O’Donnell‐Luria, Gareth Baynam, et al.. (2024). Leaving no patient behind! Expert recommendation in the use of innovative technologies for diagnosing rare diseases. Orphanet Journal of Rare Diseases. 19(1). 357–357. 7 indexed citations

Argiro, Laurent, et al.. (2024). Gastruloids are competent to specify both cardiac and skeletal muscle lineages. Nature Communications. 15(1). 10172–10172. 5 indexed citations

Özışık, Ozan, et al.. (2024). System-level analysis of genes mutated in muscular dystrophies reveals a functional pattern associated with muscle weakness distribution. Scientific Reports. 14(1). 11225–11225.

10.

Baudot, Anaı̈s, et al.. (2023). A multilevel screening pipeline in zebrafish identifies therapeutic drugs for GAN. EMBO Molecular Medicine. 15(7). e16267–e16267. 3 indexed citations

11.

Sánchez-García, Rubén J., et al.. (2023). Zoo guide to network embedding. Journal of Physics Complexity. 4(4). 42001–42001. 5 indexed citations

12.

Leutenegger, Anne‐Louise, et al.. (2023). Tracking clusters of patients over time enables extracting information from medico-administrative databases. Journal of Biomedical Informatics. 139. 104309–104309. 2 indexed citations

13.

Dion, Camille, David Hirst, Leslie Caron, et al.. (2023). In skeletal muscle and neural crest cells, SMCHD1 regulates biological pathways relevant for Bosma syndrome and facioscapulohumeral dystrophy phenotype. Nucleic Acids Research. 51(14). 7269–7287. 3 indexed citations

14.

Sánchez-Valle, Jon, Héctor Tejero, José M. Fernández, et al.. (2020). Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships. Nature Communications. 11(1). 2854–2854. 23 indexed citations

15.

Greco, Alessandro, Jon Sánchez-Valle, Véra Pancaldi, et al.. (2019). Molecular Inverse Comorbidity between Alzheimer’s Disease and Lung Cancer: New Insights from Matrix Factorization. International Journal of Molecular Sciences. 20(13). 3114–3114. 11 indexed citations

16.

Valdeolivas, Alberto, Laurent Tichit, Claire Navarro, et al.. (2018). Random walk with restart on multiplex and heterogeneous biological networks. Bioinformatics. 35(3). 497–505. 187 indexed citations

17.

Sánchez-Valle, Jon, Héctor Tejero, Kristina Ibáñez, et al.. (2017). A molecular hypothesis to explain direct and inverse co-morbidities between Alzheimer’s Disease, Glioblastoma and Lung cancer. Scientific Reports. 7(1). 4474–4474. 73 indexed citations

18.

Tripathi, Sushil, Åsmund Flobak, Konika Chawla, et al.. (2015). The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms. BMC Systems Biology. 9(1). 40–40. 44 indexed citations

19.

Glaab, Enrico, Anaı̈s Baudot, Natalio Krasnogor, & Alfonso Valencia. (2010). Extending pathways and processes using molecular interaction networks to analyse cancer genome data. BMC Bioinformatics. 11(1). 597–597. 34 indexed citations

20.

Pilot‐Storck, Fanny, Emilie Chopin, Jean‐François Rual, et al.. (2010). Interactome Mapping of the Phosphatidylinositol 3-Kinase-Mammalian Target of Rapamycin Pathway Identifies Deformed Epidermal Autoregulatory Factor-1 as a New Glycogen Synthase Kinase-3 Interactor. Molecular & Cellular Proteomics. 9(7). 1578–1593. 48 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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