David Gómez-Cabrero

13.5k total citations · 2 hit papers
104 papers, 5.6k citations indexed

About

David Gómez-Cabrero is a scholar working on Molecular Biology, Immunology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, David Gómez-Cabrero has authored 104 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 14 papers in Immunology and 13 papers in Pulmonary and Respiratory Medicine. Recurrent topics in David Gómez-Cabrero's work include Bioinformatics and Genomic Networks (16 papers), Epigenetics and DNA Methylation (13 papers) and Single-cell and spatial transcriptomics (12 papers). David Gómez-Cabrero is often cited by papers focused on Bioinformatics and Genomic Networks (16 papers), Epigenetics and DNA Methylation (13 papers) and Single-cell and spatial transcriptomics (12 papers). David Gómez-Cabrero collaborates with scholars based in Sweden, Spain and United Kingdom. David Gómez-Cabrero's co-authors include Jesper Tegnér, Francesco Marabita, Ana Conesa, Andrew E. Teschendorff, Sonia Tarazona, A Mortazavi, Stephan Beck, Thomas E. Bartlett, Matthias Lechner and Pedro Madrigal and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

David Gómez-Cabrero

99 papers receiving 5.5k citations

Hit Papers

align trajectories

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.

A survey of best practices for RNA-seq data analysis

2016 1.7k citations Ana Conesa, Sonia Tarazona et al. profile →
A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

2012 1.1k citations Francesco Marabita, Jesper Tegnér et al. profile →

Peers

David Gómez-Cabrero

GENET

IMMUN

PHYSI

Pan Du United States

Simon Lin United States

Ralf Herwig Germany

Zhijin Wu United States

Daniele Merico Canada

Michael Hubank United Kingdom

Gabriela Vaz Meirelles Brazil

Priit Adler Estonia

Zhiao Shi United States

Lin Li China

Pan Du United States

David Gómez-Cabrero

3.7k ×1.1

838 ×1.1

GENET

991 ×1.3

611 ×1.0

IMMUN

263 ×0.6

PHYSI

Citations per year, relative to David Gómez-Cabrero David Gómez-Cabrero (= 1×) peers Pan Du

Countries citing papers authored by David Gómez-Cabrero

Since Specialization

Citations

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

Fields of papers citing papers by David Gómez-Cabrero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Gómez-Cabrero. 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 David Gómez-Cabrero. The network helps show where David Gómez-Cabrero may publish in the future.

Co-authorship network of co-authors of David Gómez-Cabrero

This figure shows the co-authorship network connecting the top 25 collaborators of David Gómez-Cabrero. A scholar is included among the top collaborators of David Gómez-Cabrero 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 David Gómez-Cabrero. David Gómez-Cabrero 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

Han, Wenkai, David Gómez-Cabrero, Jesper Tegnér, et al.. (2025). Benchmarking cross-species single-cell RNA-seq data integration methods: towards a cell type tree of life. Nucleic Acids Research. 53(1). 3 indexed citations

Khan, Sameer, et al.. (2025). Multimodal foundation transformer models for multiscale genomics. Nature Methods. 23(2). 299–311.

Bagci, Hakan, Roel Oldenkamp, George R. Young, et al.. (2024). Competition shapes the landscape of X-chromosome-linked genetic diversity. Nature Genetics. 56(8). 1678–1688. 2 indexed citations

Lehmann, Robert, et al.. (2023). HLA-based banking of induced pluripotent stem cells in Saudi Arabia. Stem Cell Research & Therapy. 14(1). 374–374. 11 indexed citations

Khan, Sameer, Vincenzo Lagani, Robert Lehmann, et al.. (2023). Reusability report: Learning the transcriptional grammar in single-cell RNA-sequencing data using transformers. Nature Machine Intelligence. 5(12). 1437–1446. 13 indexed citations

Yang, Chao-Han Huck, et al.. (2023). Whispering LLaMA: A Cross-Modal Generative Error Correction Framework for Speech Recognition. 10007–10016. 10 indexed citations

Otero, Irene, Haritz Moreno, Paula Aldaz, et al.. (2022). The Regulators of Peroxisomal Acyl-Carnitine Shuttle CROT and CRAT Promote Metastasis in Melanoma. Journal of Investigative Dermatology. 143(2). 305–316.e5. 17 indexed citations

Chambon, Christophe, Eric Neyraud, Thierry Sayd, et al.. (2021). The salivary proteome reflects some traits of dietary habits in diabetic and non-diabetic older adults. European Journal of Nutrition. 60(8). 4331–4344. 6 indexed citations

Ewing, Ewoud, et al.. (2020). GeneSetCluster: a tool for summarizing and integrating gene-set analysis results. BMC Bioinformatics. 21(1). 12 indexed citations

10.

Tarazona, Sonia, Leandro Balzano‐Nogueira, David Gómez-Cabrero, et al.. (2020). Harmonization of quality metrics and power calculation in multi-omic studies. Nature Communications. 11(1). 3092–3092. 65 indexed citations

11.

Planell, Núria, Susana Ravassa, Amaia Vilas‐Zornoza, et al.. (2020). Functional and transcriptomic analysis of extracellular vesicles identifies calprotectin as a new prognostic marker in peripheral arterial disease (PAD). Journal of Extracellular Vesicles. 9(1). 1729646–1729646. 48 indexed citations

12.

Witherden, Elizabeth A., Sunjae Lee, Saeed Shoaie, et al.. (2020). Abundance and diversity of resistomes differ between healthy human oral cavities and gut. Nature Communications. 11(1). 693–693. 62 indexed citations

13.

Παπουτσόγλου, Γεώργιος, Vincenzo Lagani, Angelika Schmidt, et al.. (2019). Challenges in the Multivariate Analysis of Mass Cytometry Data: The Effect of Randomization. Cytometry Part A. 95(11). 1178–1190. 9 indexed citations

14.

Ewing, Ewoud, Lara Kular, Nestoras Karathanasis, et al.. (2019). Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression. EBioMedicine. 43. 411–423. 46 indexed citations

15.

Carlström, Karl E., Ewoud Ewing, Mathias Granqvist, et al.. (2019). Therapeutic efficacy of dimethyl fumarate in relapsing-remitting multiple sclerosis associates with ROS pathway in monocytes. Nature Communications. 10(1). 3081–3081. 107 indexed citations

16.

Gossec, Laure, Joanna Kedra, H. Servy, et al.. (2019). EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases. Annals of the Rheumatic Diseases. 79(1). 69–76. 50 indexed citations

17.

Morikawa, Hiromasa, Ewoud Ewing, Stephan Ruhrmann, et al.. (2019). Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients. Scientific Reports. 9(1). 11996–11996. 11 indexed citations

18.

Kedra, Joanna, Timothy R. D. J. Radstake, Aridaman Pandit, et al.. (2019). Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations. RMD Open. 5(2). e001004–e001004. 23 indexed citations

19.

Schmidt, Angelika, Francesco Marabita, Narsis A. Kiani, et al.. (2018). Time-resolved transcriptome and proteome landscape of human regulatory T cell (Treg) differentiation reveals novel regulators of FOXP3. BMC Biology. 16(1). 47–47. 48 indexed citations

20.

Ramos, Marcel, Lucas Schiffer, Angela Re, et al.. (2017). Software for the Integration of Multiomics Experiments in Bioconductor. Cancer Research. 77(21). e39–e42. 61 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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