Alejandro Ocampo

5.2k total citations
36 papers, 1.8k citations indexed

About

Alejandro Ocampo is a scholar working on Molecular Biology, Aging and Cellular and Molecular Neuroscience. According to data from OpenAlex, Alejandro Ocampo has authored 36 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 7 papers in Aging and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Alejandro Ocampo's work include Pluripotent Stem Cells Research (11 papers), CRISPR and Genetic Engineering (9 papers) and Mitochondrial Function and Pathology (7 papers). Alejandro Ocampo is often cited by papers focused on Pluripotent Stem Cells Research (11 papers), CRISPR and Genetic Engineering (9 papers) and Mitochondrial Function and Pathology (7 papers). Alejandro Ocampo collaborates with scholars based in United States, Switzerland and Spain. Alejandro Ocampo's co-authors include Juan Carlos Izpisúa Belmonte, Antoni Barrientos, Guang‐Hui Liu, Elizabeth A. Schroeder, Gerald S. Shadel, Xiuling Xu, Fei Yi, Shunlei Duan, Yong Pan and Ruotong Ren and has published in prestigious journals such as Nature, Cell and Nature Communications.

In The Last Decade

Alejandro Ocampo

32 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alejandro Ocampo United States	17	1.4k	360	267	175	173	36	1.8k
Oliver Dreesen Singapore	25	1.4k 1.0×	98 0.3×	466 1.7×	103 0.6×	147 0.8×	36	2.4k
Andreas Ivessa United States	17	1.8k 1.3×	183 0.5×	305 1.1×	121 0.7×	139 0.8×	31	2.3k
Qun He China	25	1.7k 1.2×	175 0.5×	267 1.0×	423 2.4×	124 0.7×	98	2.9k
Feodor D. Price Canada	11	2.0k 1.5×	135 0.4×	514 1.9×	111 0.6×	245 1.4×	16	2.4k
Emma Thomas Australia	7	562 0.4×	489 1.4×	279 1.0×	62 0.4×	42 0.2×	9	1.4k
Yuki Sugiyama Japan	22	1.6k 1.1×	74 0.2×	138 0.5×	100 0.6×	137 0.8×	41	2.6k
Xu Jiang China	26	1.4k 1.0×	118 0.3×	71 0.3×	561 3.2×	171 1.0×	59	2.1k
Jiyun Lee South Korea	24	819 0.6×	105 0.3×	119 0.4×	363 2.1×	81 0.5×	93	1.6k
Denise K. Marciano United States	22	799 0.6×	58 0.2×	144 0.5×	64 0.4×	159 0.9×	37	1.6k
Kan Cao United States	28	2.7k 2.0×	158 0.4×	334 1.3×	64 0.4×	143 0.8×	50	3.3k

Countries citing papers authored by Alejandro Ocampo

Since Specialization

Citations

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

Fields of papers citing papers by Alejandro Ocampo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alejandro Ocampo

This figure shows the co-authorship network connecting the top 25 collaborators of Alejandro Ocampo. A scholar is included among the top collaborators of Alejandro Ocampo 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 Alejandro Ocampo. Alejandro Ocampo 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

Pérez, Kevin, et al.. (2025). Lifetime age‐related changes in clinical laboratory results, aging clocks and mortality predictors in 2412 Golden Retrievers. Aging Cell. 24(4). e14438–e14438.

Paine, Patrick, et al.. (2025). Chemical reprogramming ameliorates cellular hallmarks of aging and extends lifespan. EMBO Molecular Medicine. 17(8). 2071–2094. 4 indexed citations

Pinto, Carla M. A., et al.. (2025). Comprehensive evaluation of lifespan‐extending molecules in C. elegans. Aging Cell. 24(4). e14424–e14424. 2 indexed citations

Haghani, Amin, Ake T Lu, Qi Yan, et al.. (2025). EnsembleAge: enhancing epigenetic age assessment with a multi-clock framework. GeroScience. 48(2). 2873–2886.

Picó, Sara, Alberto Parras, Gabriela Desdín-Micó, et al.. (2025). Comparative analysis of mouse strains for in vivo induction of reprogramming factors. Cell Reports. 44(7). 115879–115879.

MacArthur, Michael R., Jing Zhang, Guillermo Turiel, et al.. (2024). Nicotinamide mononucleotide restores impaired metabolism, endothelial cell proliferation and angiogenesis in old sedentary male mice. iScience. 28(1). 111656–111656. 2 indexed citations

MacArthur, Michael R., Anna Faivre, David Legouis, et al.. (2024). Short-term hypercaloric carbohydrate loading increases surgical stress resilience by inducing FGF21. Nature Communications. 15(1). 1073–1073. 2 indexed citations

Paine, Patrick, et al.. (2023). Partial cellular reprogramming: A deep dive into an emerging rejuvenation technology. Aging Cell. 23(2). e14039–e14039. 11 indexed citations

Parras, Alberto, Gabriela Desdín-Micó, Sara Picó, et al.. (2023). In vivo reprogramming leads to premature death linked to hepatic and intestinal failure. Nature Aging. 3(12). 1509–1520. 24 indexed citations

10.

Desdín-Micó, Gabriela, et al.. (2023). Vitamin B12 emerges as key player during cellular reprogramming. Nature Metabolism. 5(11). 1844–1845.

11.

Pérez, Kevin, Viviane Praz, Guillermo López García, et al.. (2023). ATAC-clock: An aging clock based on chromatin accessibility. GeroScience. 46(2). 1789–1806. 22 indexed citations

12.

Magalhães, João Pedro de & Alejandro Ocampo. (2022). Cellular reprogramming and the rise of rejuvenation biotech. Trends in biotechnology. 40(6). 639–642. 14 indexed citations

13.

Conte, Giorgia, Alberto Parras, Laura de Diego-García, et al.. (2020). High concordance between hippocampal transcriptome of the mouse intra‐amygdala kainic acid model and human temporal lobe epilepsy. Epilepsia. 61(12). 2795–2810. 24 indexed citations

14.

Kurita, Masakazu, Toshikazu Araoka, Tomoaki Hishida, et al.. (2018). In vivo reprogramming of wound-resident cells generates skin epithelial tissue. Nature. 561(7722). 243–247. 109 indexed citations

15.

Ren, Ruotong, Alejandro Ocampo, Guang‐Hui Liu, & Juan Carlos Izpisúa Belmonte. (2017). Regulation of Stem Cell Aging by Metabolism and Epigenetics. Cell Metabolism. 26(3). 460–474. 191 indexed citations

16.

Ocampo, Alejandro, Kai Ruan, Yi Zhu, et al.. (2016). Attenuation of polyglutamine-induced toxicity by enhancement of mitochondrial OXPHOS in yeast and fly models of aging. Microbial Cell. 3(8). 338–351. 11 indexed citations

17.

Aguirre, Aitor, Núria Montserrat, Serena Zacchigna, et al.. (2014). In Vivo Activation of a Conserved MicroRNA Program Induces Mammalian Heart Regeneration. Cell stem cell. 15(6). 805–805. 1 indexed citations

18.

Xu, Xiuling, Shunlei Duan, Fei Yi, et al.. (2013). Mitochondrial Regulation in Pluripotent Stem Cells. Cell Metabolism. 18(3). 325–332. 311 indexed citations

19.

Ocampo, Alejandro, Jingjing Liu, Elizabeth A. Schroeder, Gerald S. Shadel, & Antoni Barrientos. (2012). Mitochondrial Respiratory Thresholds Regulate Yeast Chronological Life Span and its Extension by Caloric Restriction. Cell Metabolism. 16(1). 55–67. 139 indexed citations

20.

Fozo, Elizabeth M., Mitsuoki Kawano, Fanette Fontaine, et al.. (2008). Repression of small toxic protein synthesis by the Sib and OhsC small RNAs. Molecular Microbiology. 70(5). 1076–1093. 134 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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