Mónica Povedano

897 total citations
16 papers, 605 citations indexed

About

Mónica Povedano is a scholar working on Neurology, Genetics and Molecular Biology. According to data from OpenAlex, Mónica Povedano has authored 16 papers receiving a total of 605 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Neurology, 7 papers in Genetics and 6 papers in Molecular Biology. Recurrent topics in Mónica Povedano's work include Amyotrophic Lateral Sclerosis Research (10 papers), Neurogenetic and Muscular Disorders Research (7 papers) and Parkinson's Disease Mechanisms and Treatments (5 papers). Mónica Povedano is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (10 papers), Neurogenetic and Muscular Disorders Research (7 papers) and Parkinson's Disease Mechanisms and Treatments (5 papers). Mónica Povedano collaborates with scholars based in Spain, Netherlands and Austria. Mónica Povedano's co-authors include Isidró Ferrer, Reinald Pamplona, Manuel Portero-Otı́n, Victòria Ayala, Mariona Jové, Daniel Cacabelos, Marı́a Josep Bellmunt, Esther Dalfó, Ekaterina V. Ilieva and Rafael Gálvez and has published in prestigious journals such as Brain, International Journal of Molecular Sciences and Journal of Neurochemistry.

In The Last Decade

Mónica Povedano

16 papers receiving 594 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mónica Povedano Spain 11 357 188 147 143 109 16 605
Olga Tarabal Spain 18 249 0.7× 295 1.6× 208 1.4× 105 0.7× 55 0.5× 27 733
Bhuvaneish T. Selvaraj United Kingdom 15 317 0.9× 354 1.9× 174 1.2× 113 0.8× 53 0.5× 30 709
Zygmunt Jamrozik Poland 13 359 1.0× 162 0.9× 52 0.4× 108 0.8× 51 0.5× 49 557
Javier H. Jara United States 14 434 1.2× 249 1.3× 271 1.8× 106 0.7× 38 0.3× 15 677
Anissa Fergani France 10 635 1.8× 271 1.4× 373 2.5× 141 1.0× 60 0.6× 10 843
Virginia Le Verche United States 8 248 0.7× 274 1.5× 154 1.0× 105 0.7× 22 0.2× 9 562
Barbara Noli Italy 17 140 0.4× 221 1.2× 70 0.5× 175 1.2× 33 0.3× 30 617
Somasish Ghosh Dastidar United States 11 179 0.5× 367 2.0× 99 0.7× 104 0.7× 61 0.6× 21 639
William Camu France 12 787 2.2× 293 1.6× 416 2.8× 152 1.1× 47 0.4× 16 957
Joanna A. Korecka Netherlands 12 208 0.6× 273 1.5× 30 0.2× 105 0.7× 52 0.5× 14 616

Countries citing papers authored by Mónica Povedano

Since Specialization
Citations

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

Fields of papers citing papers by Mónica Povedano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mónica Povedano

This figure shows the co-authorship network connecting the top 25 collaborators of Mónica Povedano. A scholar is included among the top collaborators of Mónica Povedano 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 Mónica Povedano. Mónica Povedano 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.
Andrés‐Benito, Pol, Juan F. Vázquez‐Costa, M.J. Colomina, et al.. (2024). Neurodegeneration Biomarkers in Adult Spinal Muscular Atrophy (SMA) Patients Treated with Nusinersen. International Journal of Molecular Sciences. 25(7). 3810–3810. 7 indexed citations
2.
Domínguez, Raúl, M.J. Colomina, Antonio Martı́nez-Yélamos, et al.. (2024). Increased CXCL12, a potential CSF biomarker for differential diagnosis of amyotrophic lateral sclerosis. Brain Communications. 6(4). fcae271–fcae271. 1 indexed citations
3.
Torres, Pascual, Carlos Anerillas, Omar Ramírez‐Núñez, et al.. (2022). A motor neuron disease mouse model reveals a non-canonical profile of senescence biomarkers. Disease Models & Mechanisms. 15(8). 12 indexed citations
4.
Torres, Pascual, Omar Ramírez‐Núñez, Ana Belén Granado‐Serrano, et al.. (2021). Cell Stress Induces Mislocalization of Transcription Factors with Mitochondrial Enrichment. International Journal of Molecular Sciences. 22(16). 8853–8853. 5 indexed citations
5.
Sol, Joaquím, Mariona Jové, Mónica Povedano, et al.. (2021). Lipidomic traits of plasma and cerebrospinal fluid in amyotrophic lateral sclerosis correlate with disease progression. Brain Communications. 3(3). fcab143–fcab143. 38 indexed citations
6.
Ramírez‐Núñez, Omar, Mariona Jové, Pascual Torres, et al.. (2021). Nuclear lipidome is altered in amyotrophic lateral sclerosis: A pilot study. Journal of Neurochemistry. 158(2). 482–499. 12 indexed citations
7.
Andrés‐Benito, Pol, Ellen Gelpí, Mariona Jové, et al.. (2020). Lipid alterations in human frontal cortex in ALS‐FTLD‐TDP43 proteinopathy spectrum are partly related to peroxisome impairment. Neuropathology and Applied Neurobiology. 47(4). 544–563. 15 indexed citations
8.
Torres, Pascual, Daniel Cacabelos, Kylynda C. Bauer, et al.. (2019). Gender-Specific Beneficial Effects of Docosahexaenoic Acid Dietary Supplementation in G93A-SOD1 Amyotrophic Lateral Sclerosis Mice. Neurotherapeutics. 17(1). 269–281. 19 indexed citations
9.
Andrés‐Benito, Pol, Mónica Povedano, Pascual Torres, Manuel Portero-Otı́n, & Isidró Ferrer. (2019). Altered Dynein Axonemal Assembly Factor 1 Expression in C-Boutons in Bulbar and Spinal Cord Motor-Neurons in Sporadic Amyotrophic Lateral Sclerosis. Journal of Neuropathology & Experimental Neurology. 78(5). 416–425. 4 indexed citations
10.
Torres, Pascual, Omar Ramírez‐Núñez, Ricardo Romero‐Guevara, et al.. (2018). Cryptic exon splicing function of TARDBP interacts with autophagy in nervous tissue. Autophagy. 14(8). 1398–1403. 38 indexed citations
11.
Andrés‐Benito, Pol, Raúl Domínguez, M.J. Colomina, et al.. (2018). YKL40 in sporadic amyotrophic lateral sclerosis: cerebrospinal fluid levels as a prognosis marker of disease progression. Aging. 10(9). 2367–2382. 29 indexed citations
12.
Cacabelos, Daniel, Omar Ramírez‐Núñez, Ana Belén Granado‐Serrano, et al.. (2016). Early and gender-specific differences in spinal cord mitochondrial function and oxidative stress markers in a mouse model of ALS. Acta Neuropathologica Communications. 4(1). 3–3. 40 indexed citations
13.
Casasnovas, Carlos, Isabel Banchs, Maria Alberti, et al.. (2011). A novel small deletion in PMP22 causes a mild hereditary neuropathy with liability to pressure palsies phenotype. Muscle & Nerve. 45(1). 135–138. 10 indexed citations
14.
Ilieva, Ekaterina V., Victòria Ayala, Mariona Jové, et al.. (2007). Oxidative and endoplasmic reticulum stress interplay in sporadic amyotrophic lateral sclerosis. Brain. 130(12). 3111–3123. 272 indexed citations
15.
Montero, J., et al.. (2006). Electrophysiological study of ephaptic axono‐axonal responses in hemifacial spasm. Muscle & Nerve. 35(2). 184–188. 33 indexed citations
16.
Povedano, Mónica, Jordi Gascón, Rafael Gálvez, Manuel Ruiz‐Aravena, & Javier Rejas. (2006). Cognitive Function Impairment in Patients with Neuropathic Pain Under Standard Conditions of Care. Journal of Pain and Symptom Management. 33(1). 78–89. 70 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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