Carlos Torroja

8.4k total citations
33 papers, 1.7k citations indexed

About

Carlos Torroja is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Carlos Torroja has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 6 papers in Immunology and 5 papers in Genetics. Recurrent topics in Carlos Torroja's work include Hedgehog Signaling Pathway Studies (6 papers), Single-cell and spatial transcriptomics (5 papers) and Congenital heart defects research (5 papers). Carlos Torroja is often cited by papers focused on Hedgehog Signaling Pathway Studies (6 papers), Single-cell and spatial transcriptomics (5 papers) and Congenital heart defects research (5 papers). Carlos Torroja collaborates with scholars based in Spain, United Kingdom and Germany. Carlos Torroja's co-authors include Isabel Guerrero, Fátima Sánchez‐Cabo, Nicole Gorfinkiel, Enrique Lara‐Pezzi, Girolamo Giudice, Ainhoa Callejo, Verónica Martı́n, Luis Quijada, Joan Isern and Lorena Arranz and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Circulation.

In The Last Decade

Carlos Torroja

32 papers receiving 1.7k citations

Peers

Carlos Torroja
Soonsang Yoon United States
Pallavi Bhattaram United States
Christel Kockx Netherlands
Alison Miyamoto United States
Garrett C. Heffner United States
Matthew Kofron United States
Malkiel A. Cohen United States
Soonsang Yoon United States
Carlos Torroja
Citations per year, relative to Carlos Torroja Carlos Torroja (= 1×) peers Soonsang Yoon

Countries citing papers authored by Carlos Torroja

Since Specialization
Citations

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

Fields of papers citing papers by Carlos Torroja

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Torroja

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Torroja. A scholar is included among the top collaborators of Carlos Torroja 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 Carlos Torroja. Carlos Torroja 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.
Torroja, Carlos, Daniel Morales‐Cano, Rubén Mota, et al.. (2025). Atherosclerotic disease activity is associated with glycolytic enzyme expression across multiple cell types and is trackable by FDG-PET. Science Translational Medicine. 17(811). eado6467–eado6467. 2 indexed citations
2.
Soto‐Heredero, Gonzalo, Enrique Gabandé‐Rodríguez, Elisa Carrasco, et al.. (2025). KLRG1 identifies regulatory T cells with mitochondrial alterations that accumulate with aging. Nature Aging. 5(5). 799–815. 7 indexed citations
3.
Monte-Monge, Alberto Del, Pilar Gonzalo, María J. Andrés‐Manzano, et al.. (2025). Lamin A/C Expression in Hematopoietic Cells Declines During Human Aging and Constrains Atherosclerosis in Mice. Arteriosclerosis Thrombosis and Vascular Biology. 45(9). 1616–1635. 1 indexed citations
4.
Barettino, Ana, Cristina González‐Gómez, Pilar Gonzalo, et al.. (2024). Endothelial YAP/TAZ activation promotes atherosclerosis in a mouse model of Hutchinson-Gilford progeria syndrome. Journal of Clinical Investigation. 134(22). 8 indexed citations
5.
Hamczyk, Magda R., Rosa M. Nevado, Pilar Gonzalo, et al.. (2024). Endothelial-to-Mesenchymal Transition Contributes to Accelerated Atherosclerosis in Hutchinson-Gilford Progeria Syndrome. Circulation. 150(20). 1612–1630. 8 indexed citations
6.
Arco, Pablo Gómez‐del, Joan Isern, Daniel Jiménez‐Carretero, et al.. (2024). The G4 resolvase Dhx36 modulates cardiomyocyte differentiation and ventricular conduction system development. Nature Communications. 15(1). 8602–8602. 1 indexed citations
7.
Carramolino, Laura, Julián Albarrán-Juárez, Esther Hernández‐SanMiguel, et al.. (2024). Cholesterol lowering depletes atherosclerotic lesions of smooth muscle cell-derived fibromyocytes and chondromyocytes. Nature Cardiovascular Research. 3(2). 203–220. 10 indexed citations
8.
Tiana, María, Elena López‐Jiménez, Julio Sainz de Aja, et al.. (2022). Pluripotency factors regulate the onset of Hox cluster activation in the early embryo. Science Advances. 8(28). eabo3583–eabo3583. 9 indexed citations
9.
Marques, Inês J., Alexander Ernst, Andrés Sanz-Morejón, et al.. (2022). Wt1 transcription factor impairs cardiomyocyte specification and drives a phenotypic switch from myocardium to epicardium. Development. 149(6). 11 indexed citations
10.
Marques, Inês J., Andrés Sanz-Morejón, Uta Naumann, et al.. (2022). WT1 transcription factor impairs cardiomyocyte specification and drives a phenotypic switch from myocardium to epicardium. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
11.
Sánchez-Iranzo, Héctor, Wajid Jawaid, Sergio Menchero, et al.. (2019). Nanog regulates Pou3f1 expression at the exit from pluripotency during gastrulation. Biology Open. 8(11). 9 indexed citations
12.
Álvarez-Prado, Ángel F., Pablo Pérez‐Durán, Arantxa Pérez‐García, et al.. (2018). A broad atlas of somatic hypermutation allows prediction of activation-induced deaminase targets. The Journal of Experimental Medicine. 215(3). 761–771. 64 indexed citations
13.
Acín‐Pérez, Rebeca, Ana Victoria Lechuga‐Vieco, Rocío Nieto-Arellano, et al.. (2018). Ablation of the stress protease OMA1 protects against heart failure in mice. Science Translational Medicine. 10(434). 64 indexed citations
14.
Gómez-Velázquez, Melisa, Ana Victoria Lechuga‐Vieco, Rocío Nieto-Arellano, et al.. (2017). CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart. PLoS Genetics. 13(8). e1006985–e1006985. 44 indexed citations
15.
Patowary, Ashok, Meghna Singh, Rajendra Chauhan, et al.. (2013). A Sequence-Based Variation Map of Zebrafish. Zebrafish. 10(1). 15–20. 34 indexed citations
16.
Callejo, Ainhoa, Nicole Gorfinkiel, Germán Andrés, et al.. (2011). Dispatched mediates Hedgehog basolateral release to form the long-range morphogenetic gradient in the Drosophila wing disk epithelium. Proceedings of the National Academy of Sciences. 108(31). 12591–12598. 129 indexed citations
17.
Cañón, Susana, Teresa Rayón, Bárbara Pernaute, et al.. (2010). Evolution of the mammalian embryonic pluripotency gene regulatory network. Proceedings of the National Academy of Sciences. 107(46). 19955–19960. 29 indexed citations
18.
Torroja, Carlos, Nicole Gorfinkiel, & Isabel Guerrero. (2005). Mechanisms of Hedgehog gradient formation and interpretation. Journal of Neurobiology. 64(4). 334–356. 72 indexed citations
19.
Torroja, Carlos, Nicole Gorfinkiel, & Isabel Guerrero. (2004). Patched controls the Hedgehog gradient by endocytosis in a dynamin-dependent manner, but this internalization does not play a major role in signal transduction. Development. 131(10). 2395–2408. 142 indexed citations
20.
Martı́n, Verónica, et al.. (2001). The sterol-sensing domain of Patched protein seems to control Smoothened activity through Patched vesicular trafficking. Current Biology. 11(8). 601–607. 153 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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