David Gómez-Cabrero
- Cancer Research top 2%
- Cancer-related molecular mechanisms research 6
- Molecular Biology top 2%
- Bioinformatics and Genomic Networks 16
- Epigenetics and DNA Methylation 13
- Single-cell and spatial transcriptomics 12
- Gene expression and cancer classification 11
- Gene Regulatory Network Analysis 6
- Immunology top 5%
- Genetics top 2%
- Biological Psychiatry top 10%
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- Chronic Obstructive Pulmonary Disease (COPD) Research 10
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- Chronic Disease Management Strategies 5
- Co-authors
- Jesper TegnérFrancesco MarabitaAna ConesaAndrew E. TeschendorffSonia TarazonaA MortazaviStephan BeckThomas E. Bartlett
- Journals
- Journal of Translational Medicine (11 papers)BMC Bioinformatics (6 papers)Nature Communications (4 papers)
- Partner nations
- SwedenSpainUnited Kingdom
In The Last Decade
David Gómez-Cabrero
99 papers receiving 5.5k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Cancer Research 778
- Molecular Biology 3.4k
- Immunology 610
- Genetics 781
- Biological Psychiatry 54
Countries citing papers authored by David Gómez-Cabrero
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
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
The 25 scholars most cited alongside David Gómez-Cabrero, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 11 | |
| 5 | 2023 | 13 | |
| 6 | 2023 | 10 | |
| 7 | 2022 | 17 | |
| 8 | 2021 | 6 | |
| 9 | 2020 | 12 | |
| 10 | 2020 | 65 | |
| 11 | 2020 | 48 | |
| 12 | 2020 | 62 | |
| 13 | 2019 | 9 | |
| 14 | 2019 | 46 | |
| 15 | 2019 | 107 | |
| 16 | 2019 | 50 | |
| 17 | 2019 | 11 | |
| 18 | 2019 | 23 | |
| 19 | 2018 | 48 | |
| 20 | 2017 | 61 |
About David Gómez-Cabrero
David Gómez-Cabrero is a scholar working on Health Informatics, Geriatrics and Gerontology and Family Practice, having authored 104 papers that have together received 5.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (16 papers), Epigenetics and DNA Methylation (13 papers), Single-cell and spatial transcriptomics (12 papers), Gene expression and cancer classification (11 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (10 papers), Cancer-related molecular mechanisms research (6 papers), Gene Regulatory Network Analysis (6 papers) and Chronic Disease Management Strategies (5 papers). The work is most often cited by research in Cancer Research (778 citations), Molecular Biology (3.4k citations) and Immunology (610 citations). David Gómez-Cabrero has collaborated with scholars based in Sweden, Spain and United Kingdom. Frequent 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. Their work appears in journals such as Journal of Translational Medicine, BMC Bioinformatics, Nature Communications, Nucleic Acids Research and Epigenetics.
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.