Matheus B. Victor

3.0k total citations · 2 hit papers
16 papers, 1.4k citations indexed

About

Matheus B. Victor is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Matheus B. Victor has authored 16 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Neurology and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Matheus B. Victor's work include Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Pluripotent Stem Cells Research (4 papers) and Alzheimer's disease research and treatments (3 papers). Matheus B. Victor is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Pluripotent Stem Cells Research (4 papers) and Alzheimer's disease research and treatments (3 papers). Matheus B. Victor collaborates with scholars based in United States, Canada and Finland. Matheus B. Victor's co-authors include Andrew S. Yoo, Michelle Richner, Li‐Huei Tsai, Christine J. Huh, Bo Zhang, Manolis Kellis, Joel Blanchard, Jeanne M. Nerbonne, Tracey O. Hermanstyne and Pan‐Yue Deng and has published in prestigious journals such as Cell, Nature Medicine and Neuron.

In The Last Decade

Matheus B. Victor

15 papers receiving 1.4k citations

Hit Papers

Human microglial state dynamics in Alzheimer’s disease pr... 2022 2026 2023 2024 2023 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matheus B. Victor United States 12 877 386 359 324 176 16 1.4k
Charles Arber United Kingdom 16 642 0.7× 294 0.8× 331 0.9× 351 1.1× 183 1.0× 32 1.1k
Julia TCW United States 15 633 0.7× 302 0.8× 210 0.6× 394 1.2× 165 0.9× 25 1.1k
Bilal E. Kerman United States 10 646 0.7× 328 0.8× 337 0.9× 145 0.4× 293 1.7× 31 1.3k
Galina Erikson United States 15 759 0.9× 372 1.0× 220 0.6× 234 0.7× 148 0.8× 23 1.4k
Jessica E. Young United States 20 1.2k 1.4× 207 0.5× 772 2.2× 586 1.8× 121 0.7× 52 1.9k
Minna Oksanen Finland 10 424 0.5× 360 0.9× 262 0.7× 307 0.9× 129 0.7× 18 954
Satyan Chintawar Belgium 11 542 0.6× 306 0.8× 327 0.9× 129 0.4× 175 1.0× 13 976
Paulo D. Koeberle Canada 22 810 0.9× 316 0.8× 656 1.8× 163 0.5× 222 1.3× 33 1.5k
Mathéa Pietri France 14 636 0.7× 286 0.7× 252 0.7× 212 0.7× 54 0.3× 22 1.0k
Monique Pena United States 6 583 0.7× 683 1.8× 180 0.5× 185 0.6× 220 1.3× 7 1.3k

Countries citing papers authored by Matheus B. Victor

Since Specialization
Citations

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

Fields of papers citing papers by Matheus B. Victor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matheus B. Victor. 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 Matheus B. Victor. The network helps show where Matheus B. Victor may publish in the future.

Co-authorship network of co-authors of Matheus B. Victor

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

All Works

16 of 16 papers shown
1.
Raghavan, Deepa, et al.. (2025). Microglia response and function in a chronic model of photoreceptor damage. Frontiers in Cell and Developmental Biology. 13. 1699271–1699271.
2.
Xiong, Xushen, Benjamin T. James, Carles A. Boix, et al.. (2023). Epigenomic dissection of Alzheimer’s disease pinpoints causal variants and reveals epigenome erosion. Cell. 186(20). 4422–4437.e21. 68 indexed citations
3.
Sun, Na, Matheus B. Victor, Yongjin Park, et al.. (2023). Human microglial state dynamics in Alzheimer’s disease progression. Cell. 186(20). 4386–4403.e29. 162 indexed citations breakdown →
4.
Lee, Seong Won, Young Mi Oh, Matheus B. Victor, et al.. (2023). Longitudinal modeling of human neuronal aging reveals the contribution of the RCAN1–TFEB pathway to Huntington’s disease neurodegeneration. Nature Aging. 4(1). 95–109. 10 indexed citations
5.
Welch, Gwyneth, Carles A. Boix, José Dávila-Velderrain, et al.. (2022). Neurons burdened by DNA double-strand breaks incite microglia activation through antiviral-like signaling in neurodegeneration. Science Advances. 8(39). eabo4662–eabo4662. 54 indexed citations
6.
Victor, Matheus B., Noelle Leary, Hiruy S. Meharena, et al.. (2022). Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity. Cell stem cell. 29(8). 1197–1212.e8. 154 indexed citations breakdown →
7.
Blanchard, Joel, Matheus B. Victor, & Li‐Huei Tsai. (2021). Dissecting the complexities of Alzheimer disease with in vitro models of the human brain. Nature Reviews Neurology. 18(1). 25–39. 46 indexed citations
8.
Blanchard, Joel, Michael Bula, José Dávila-Velderrain, et al.. (2021). Author Correction: Reconstruction of the human blood–brain barrier in vitro reveals a pathogenic mechanism of APOE4 in pericytes. Nature Medicine. 27(2). 356–356. 4 indexed citations
9.
Blanchard, Joel, Michael Bula, José Dávila-Velderrain, et al.. (2020). Reconstruction of the human blood–brain barrier in vitro reveals a pathogenic mechanism of APOE4 in pericytes. Nature Medicine. 26(6). 952–963. 182 indexed citations
10.
Victor, Matheus B., Michelle Richner, Seong Won Lee, et al.. (2020). Author Correction: Striatal neurons directly converted from Huntington’s disease patient fibroblasts recapitulate age-associated disease phenotypes. Nature Neuroscience. 23(10). 1307–1307. 6 indexed citations
11.
Fox, Leora M., Christopher W. Johnson, Shawei Chen, et al.. (2019). Huntington’s Disease Pathogenesis Is Modified In Vivo by Alfy/Wdfy3 and Selective Macroautophagy. Neuron. 105(5). 813–821.e6. 52 indexed citations
12.
Victor, Matheus B., Michelle Richner, Seong Won Lee, et al.. (2018). Striatal neurons directly converted from Huntington’s disease patient fibroblasts recapitulate age-associated disease phenotypes. Nature Neuroscience. 21(3). 341–352. 176 indexed citations
13.
McCoy, Matthew J., Matheus B. Victor, Michelle Richner, et al.. (2018). LONGO: an R package for interactive gene length dependent analysis for neuronal identity. Bioinformatics. 34(13). i422–i428. 16 indexed citations
14.
Huh, Christine J., Bo Zhang, Matheus B. Victor, et al.. (2016). Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts. eLife. 5. 153 indexed citations
15.
Richner, Michelle, Matheus B. Victor, Yangjian Liu, Daniel G. Abernathy, & Andrew S. Yoo. (2015). MicroRNA-based conversion of human fibroblasts into striatal medium spiny neurons. Nature Protocols. 10(10). 1543–1555. 64 indexed citations
16.
Victor, Matheus B., Michelle Richner, Tracey O. Hermanstyne, et al.. (2014). Generation of Human Striatal Neurons by MicroRNA-Dependent Direct Conversion of Fibroblasts. Neuron. 84(2). 311–323. 227 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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