Pilar Cacheiro

1.3k total citations · 1 hit paper
15 papers, 354 citations indexed

About

Pilar Cacheiro is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Pilar Cacheiro has authored 15 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Genetics and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Pilar Cacheiro's work include Genomics and Rare Diseases (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Mitochondrial Function and Pathology (2 papers). Pilar Cacheiro is often cited by papers focused on Genomics and Rare Diseases (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Mitochondrial Function and Pathology (2 papers). Pilar Cacheiro collaborates with scholars based in United Kingdom, Spain and United States. Pilar Cacheiro's co-authors include Damian Smedley, Melissa Haendel, Ángel Carracedo, Helen Parkinson, Robert Wilson, Federico López, Tudor Groza, Sara Wells, Violeta Muñoz‐Fuentes and Ann‐Marie Mallon and has published in prestigious journals such as Nucleic Acids Research, Brain and Journal of the Neurological Sciences.

In The Last Decade

Pilar Cacheiro

13 papers receiving 352 citations

Hit Papers

The International Mouse Phenotyping Consortium: comprehen... 2022 2026 2023 2024 2022 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease
    2022 171 citations Tudor Groza, Federico López et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pilar Cacheiro United Kingdom 7 228 103 67 41 27 15 354
Koichiro Doi Japan 11 251 1.1× 79 0.8× 66 1.0× 84 2.0× 21 0.8× 28 382
Bader Alhaddad Germany 15 331 1.5× 174 1.7× 69 1.0× 54 1.3× 20 0.7× 29 516
M. Reza Jabalameli United Kingdom 10 147 0.6× 82 0.8× 65 1.0× 66 1.6× 17 0.6× 18 312
Lijia Huang Canada 14 370 1.6× 180 1.7× 101 1.5× 27 0.7× 37 1.4× 32 541
Huijie Feng United States 9 201 0.9× 89 0.9× 56 0.8× 66 1.6× 69 2.6× 22 405
Mazhor Aldosary Saudi Arabia 10 386 1.7× 93 0.9× 47 0.7× 16 0.4× 22 0.8× 17 454
Emmanuelle Ranza Switzerland 12 137 0.6× 103 1.0× 36 0.5× 18 0.4× 14 0.5× 22 295
Daniel Nachun United States 11 193 0.8× 64 0.6× 58 0.9× 19 0.5× 17 0.6× 16 300
Maximilianos Elkouris Greece 7 249 1.1× 39 0.4× 58 0.9× 25 0.6× 67 2.5× 11 361
L. Frati Italy 8 207 0.9× 185 1.8× 83 1.2× 20 0.5× 30 1.1× 16 426

Countries citing papers authored by Pilar Cacheiro

Since Specialization
Citations

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

Fields of papers citing papers by Pilar Cacheiro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pilar Cacheiro

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

All Works

15 of 15 papers shown
1.
Wilson, Robert, Min‐Yen Kan, Piia Keskivali-Bond, et al.. (2025). International Mouse Phenotyping Consortium Portal: facilitating investigation of gene function and providing insights into human disease. Nucleic Acids Research. 54(D1). D1133–D1142.
2.
Duyzend, Michael, Pilar Cacheiro, Julius O.B. Jacobsen, et al.. (2024). Improving prenatal diagnosis through standards and aggregation. Prenatal Diagnosis. 44(4). 454–464. 3 indexed citations
3.
Cacheiro, Pilar, Ignatia B. Van den Veyver, Stephen A. Murray, et al.. (2024). Lethal phenotypes in Mendelian disorders. Genetics in Medicine. 26(7). 101141–101141. 1 indexed citations
4.
Cacheiro, Pilar, et al.. (2024). Computational identification of disease models through cross-species phenotype comparison. Disease Models & Mechanisms. 17(6). 5 indexed citations
5.
Cacheiro, Pilar, Nadine Spielmann, Helmut Fuchs, et al.. (2023). Knockout mice are an important tool for human monogenic heart disease studies. Disease Models & Mechanisms. 16(5). 4 indexed citations
6.
Cacheiro, Pilar & Damian Smedley. (2023). Essential genes: a cross-species perspective. Mammalian Genome. 34(3). 357–363. 2 indexed citations
7.
Groza, Tudor, Federico López, Violeta Muñoz‐Fuentes, et al.. (2022). The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease. Nucleic Acids Research. 51(D1). D1038–D1045. 171 indexed citations breakdown →
8.
Lorenzo-Arribas, Altea & Pilar Cacheiro. (2020). Florence Nightingale's Network: Women, Power, and Scientific Collaboration. Significance. 17(2). 22–25.
9.
Cacheiro, Pilar, Melissa Haendel, & Damian Smedley. (2019). New models for human disease from the International Mouse Phenotyping Consortium. Mammalian Genome. 30(5-6). 143–150. 43 indexed citations
10.
Cacheiro, Pilar, Andrés Ordóñez‐Ugalde, Beatriz Quintáns, et al.. (2017). Evaluating the Calling Performance of a Rare Disease NGS Panel for Single Nucleotide and Copy Number Variants. Molecular Diagnosis & Therapy. 21(3). 303–313. 6 indexed citations
11.
Sesar, Ángel, Pilar Cacheiro, Marisol López, et al.. (2016). Synaptotagmin XI in Parkinson's disease: New evidence from an association study in Spain and Mexico. Journal of the Neurological Sciences. 362. 321–325. 18 indexed citations
12.
Quintáns, Beatriz, Andrés Ordóñez‐Ugalde, Pilar Cacheiro, Ángel Carracedo, & María‐Jesús Sobrido. (2014). Medical genomics: The intricate path from genetic variant identification to clinical interpretation. PubMed. 3(3). 60–67. 23 indexed citations
13.
García-Murias, María, Beatriz Quintáns, Manuel Arias, et al.. (2012). ‘Costa da Morte’ ataxia is spinocerebellar ataxia 36: clinical and genetic characterization. Brain. 135(5). 1423–1435. 64 indexed citations
14.
Sobrido, María‐Jesús, Pilar Cacheiro, Ángel Carracedo, & Lars Bertram. (2012). Databases for neurogenetics: Introduction, overview, and challenges. Human Mutation. 33(9). 1311–1314. 3 indexed citations
15.
Sintas, Cèlia, Jessica Fernández‐Morales, Pilar Cacheiro, et al.. (2012). A replication study of a GWAS finding in migraine does not identify association in a Spanish case-control sample. Cephalalgia. 32(14). 1076–1080. 11 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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