Léo Machado

988 total citations
10 papers, 600 citations indexed

About

Léo Machado is a scholar working on Molecular Biology, Physiology and Biomedical Engineering. According to data from OpenAlex, Léo Machado has authored 10 papers receiving a total of 600 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Physiology and 2 papers in Biomedical Engineering. Recurrent topics in Léo Machado's work include Muscle Physiology and Disorders (8 papers), Single-cell and spatial transcriptomics (3 papers) and RNA modifications and cancer (2 papers). Léo Machado is often cited by papers focused on Muscle Physiology and Disorders (8 papers), Single-cell and spatial transcriptomics (3 papers) and RNA modifications and cancer (2 papers). Léo Machado collaborates with scholars based in France, United States and Belgium. Léo Machado's co-authors include Frédéric Relaix, Philippos Mourikis, David Castel, Rachel Legendre, David E. Birk, Meryem B. Baghdadi, So‐ichiro Fukada, Hugo Varet, Shahragim Tajbakhsh and Joana Esteves de Lima and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Léo Machado

10 papers receiving 598 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Léo Machado France	7	513	146	127	88	58	10	600
Meryem B. Baghdadi France	8	435 0.8×	97 0.7×	166 1.3×	75 0.9×	61 1.1×	8	565
Sophie Liot France	7	418 0.8×	152 1.0×	133 1.0×	104 1.2×	43 0.7×	10	594
Virginie Jacquemin France	9	521 1.0×	148 1.0×	107 0.8×	70 0.8×	87 1.5×	11	611
Suchitra D. Gopinath India	8	475 0.9×	166 1.1×	113 0.9×	110 1.3×	72 1.2×	11	604
Brendan Evano France	8	431 0.8×	117 0.8×	69 0.5×	66 0.8×	39 0.7×	11	498
Grégoire Vallet France	2	405 0.8×	120 0.8×	174 1.4×	131 1.5×	70 1.2×	2	513
Nathan C. Jones United States	6	491 1.0×	132 0.9×	108 0.9×	70 0.8×	85 1.5×	9	549
Pascal Stuelsatz United States	12	494 1.0×	181 1.2×	156 1.2×	128 1.5×	83 1.4×	17	599
James S. Novak United States	14	599 1.2×	154 1.1×	74 0.6×	92 1.0×	49 0.8×	21	678
Sharon Soueid‐Baumgarten Israel	6	321 0.6×	105 0.7×	60 0.5×	60 0.7×	52 0.9×	8	435

Countries citing papers authored by Léo Machado

Since Specialization

Citations

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

Fields of papers citing papers by Léo Machado

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Léo Machado

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

All Works

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10 of 10 papers shown

Borok, Matthew J., et al.. (2023). Unfractionated Bulk Culture of Mouse Skeletal Muscle to Recapitulate Niche and Stem Cell Quiescence. Journal of Visualized Experiments. 1 indexed citations

Benjamin, Daniel I., Joel S. Benjamin, Jengmin Kang, et al.. (2022). Fasting induces a highly resilient deep quiescent state in muscle stem cells via ketone body signaling. Cell Metabolism. 34(6). 902–918.e6. 47 indexed citations

Machado, Léo, Frédéric Relaix, & Philippos Mourikis. (2021). Stress relief: emerging methods to mitigate dissociation-induced artefacts. Trends in Cell Biology. 31(11). 888–897. 30 indexed citations

Santos, Matthieu Dos, Stéphanie Backer, Léo Machado, et al.. (2021). Extraction and sequencing of single nuclei from murine skeletal muscles. STAR Protocols. 2(3). 100694–100694. 17 indexed citations

Lima, Joana Esteves de, et al.. (2021). HIRA stabilizes skeletal muscle lineage identity. Nature Communications. 12(1). 3450–3450. 22 indexed citations

Machado, Léo, J. Camps, Matthieu Dos Santos, et al.. (2021). Tissue damage induces a conserved stress response that initiates quiescent muscle stem cell activation. Cell stem cell. 28(6). 1125–1135.e7. 88 indexed citations

Machado, Léo, Matthieu Dos Santos, J. Camps, et al.. (2020). Skeletal Muscle Tissue Damage Leads to a Conserved Stress Response and Stem Cell-Specific Adaptive Transitions. SSRN Electronic Journal. 3 indexed citations

Baghdadi, Meryem B., David Castel, Léo Machado, et al.. (2018). Reciprocal signalling by Notch–Collagen V–CALCR retains muscle stem cells in their niche. Nature. 557(7707). 714–718. 193 indexed citations

Filareto, Antonio, et al.. (2018). Monitoring disease activity noninvasively in the mdx model of Duchenne muscular dystrophy. Proceedings of the National Academy of Sciences. 115(30). 7741–7746. 5 indexed citations

10.

Machado, Léo, Joana Esteves de Lima, Odile Fabre, et al.. (2017). In Situ Fixation Redefines Quiescence and Early Activation of Skeletal Muscle Stem Cells. Cell Reports. 21(7). 1982–1993. 194 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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