Diego García‐Gómez

1.9k total citations
57 papers, 1.5k citations indexed

About

Diego García‐Gómez is a scholar working on Spectroscopy, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, Diego García‐Gómez has authored 57 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Spectroscopy, 29 papers in Biomedical Engineering and 19 papers in Molecular Biology. Recurrent topics in Diego García‐Gómez's work include Analytical Chemistry and Chromatography (27 papers), Advanced Chemical Sensor Technologies (20 papers) and Metabolomics and Mass Spectrometry Studies (12 papers). Diego García‐Gómez is often cited by papers focused on Analytical Chemistry and Chromatography (27 papers), Advanced Chemical Sensor Technologies (20 papers) and Metabolomics and Mass Spectrometry Studies (12 papers). Diego García‐Gómez collaborates with scholars based in Spain, Switzerland and Italy. Diego García‐Gómez's co-authors include Encarnación Rodríguez‐Gonzalo, R. Carabias-Martı́nez, Renato Zenobi, Pablo Sinues, Malcolm Kohler, Soledad Rubio, Javier Domínguez‐Álvarez, Lukas Bregy, Thomas Gaisl and Guillermo Vidal‐de‐Miguel and has published in prestigious journals such as Environmental Science & Technology, Analytical Chemistry and Analytical Biochemistry.

In The Last Decade

Diego García‐Gómez

54 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diego García‐Gómez Spain 23 591 580 559 214 189 57 1.5k
Νikolaos Raikos Greece 27 735 1.2× 609 1.1× 278 0.5× 115 0.5× 497 2.6× 91 2.1k
Rafał Głowacki Poland 29 683 1.2× 420 0.7× 183 0.3× 211 1.0× 135 0.7× 106 2.7k
Drupad K. Trivedi United Kingdom 21 929 1.6× 183 0.3× 440 0.8× 242 1.1× 80 0.4× 44 1.7k
Yunyun Yang China 29 562 1.0× 905 1.6× 336 0.6× 145 0.7× 646 3.4× 75 2.1k
Edward Bald Poland 31 579 1.0× 430 0.7× 165 0.3× 176 0.8× 185 1.0× 86 2.5k
Isabelle Köhler Netherlands 22 638 1.1× 582 1.0× 312 0.6× 156 0.7× 235 1.2× 59 1.3k
Jianping Xie China 23 343 0.6× 237 0.4× 289 0.5× 92 0.4× 147 0.8× 100 1.2k
Qi Zhao China 26 412 0.7× 333 0.6× 255 0.5× 85 0.4× 531 2.8× 59 1.8k
Manfred Kollroser Austria 25 741 1.3× 339 0.6× 127 0.2× 248 1.2× 168 0.9× 48 1.7k

Countries citing papers authored by Diego García‐Gómez

Since Specialization
Citations

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

Fields of papers citing papers by Diego García‐Gómez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diego García‐Gómez. 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 Diego García‐Gómez. The network helps show where Diego García‐Gómez may publish in the future.

Co-authorship network of co-authors of Diego García‐Gómez

This figure shows the co-authorship network connecting the top 25 collaborators of Diego García‐Gómez. A scholar is included among the top collaborators of Diego García‐Gómez 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 Diego García‐Gómez. Diego García‐Gómez 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.
Ballester-Caudet, Ana, et al.. (2025). Pharmacokinetic profile of metabolites by heart-cutting two-dimensional liquid chromatography: A focus on paracetamol analysis. Journal of Chromatography A. 1745. 465760–465760.
2.
Caballero‐Casero, Noelia, Diego García‐Gómez, José Luis Pérez Pavón, & Encarnación Rodríguez‐Gonzalo. (2024). Heart-Cutting Bidimensional Liquid Chromatography for the Simultaneous Analysis of Veterinary Drugs Residues and Nucleotide Monophosphates in Sheep’s Milk. Foods. 13(6). 872–872. 2 indexed citations
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Sinues, Pablo, et al.. (2023). UHPLC-MS/MS-Based Identity Confirmation of Amino Acids Involved in Response to and Side Effects from Antiseizure Medications. Journal of Proteome Research. 22(3). 990–995. 4 indexed citations
6.
Arnold, Kim, Philippe Dehio, Jonas Lötscher, et al.. (2023). Real-Time Volatile Metabolomics Analysis of Dendritic Cells. Analytical Chemistry. 95(25). 9415–9421. 5 indexed citations
7.
Sinues, Pablo, et al.. (2021). Real-time pharmacokinetics via online analysis of exhaled breath. Journal of Pharmaceutical and Biomedical Analysis. 205. 114311–114311. 10 indexed citations
8.
García‐Gómez, Diego, et al.. (2018). SUPRAS extraction approach for matrix-independent determination of amphetamine-type stimulants by LC-MS/MS. Talanta. 182. 574–582. 49 indexed citations
9.
Bregy, Lukas, Yvonne Nussbaumer‐Ochsner, Pablo Sinues, et al.. (2018). Real-time mass spectrometric identification of metabolites characteristic of chronic obstructive pulmonary disease in exhaled breath. PubMed. 7. 29–35. 53 indexed citations
10.
Gaugg, Martin Thomas, Diego García‐Gómez, Guillermo Vidal‐de‐Miguel, et al.. (2016). Expanding metabolite coverage of real-time breath analysis by coupling a universal secondary electrospray ionization source and high resolution mass spectrometry—a pilot study on tobacco smokers. Journal of Breath Research. 10(1). 16010–16010. 61 indexed citations
11.
García‐Gómez, Diego, et al.. (2016). Multicore Magnetic Nanoparticles Coated with Oligomeric Micelles: Characterization and Potential for the Extraction of Contaminants over a Wide Polarity Range. Analytical Chemistry. 89(2). 1353–1361. 12 indexed citations
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Rodríguez‐Gonzalo, Encarnación, et al.. (2013). Capillary electrophoresis–mass spectrometry for direct determination of urinary modified nucleosides. Evaluation of synthetic urine as a surrogate matrix for quantitative analysis. Journal of Chromatography B. 942-943. 21–30. 25 indexed citations
16.
Domínguez‐Álvarez, Javier, et al.. (2013). Capillary electrophoresis coupled to mass spectrometry for the determination of anthelmintic benzimidazoles in eggs using a QuEChERS with preconcentration as sample treatment. Journal of Chromatography A. 1278. 166–174. 68 indexed citations
17.
Rodríguez‐Gonzalo, Encarnación, et al.. (2013). Development of a procedure for the isolation and enrichment of modified nucleosides and nucleobases from urine prior to their determination by capillary electrophoresis–mass spectrometry. Journal of Pharmaceutical and Biomedical Analysis. 88. 489–496. 14 indexed citations
18.
García‐Gómez, Diego, et al.. (2012). A fast and reliable method for the quantitative determination of benzimidazoles and metabolites in milk by LC-MS/MS with on-line sample treatment. Analytical and Bioanalytical Chemistry. 404(10). 2909–2914. 16 indexed citations
19.
Rodríguez‐Gonzalo, Encarnación, et al.. (2010). Determination of endocrine disruptors in honey by CZE‐MS using restricted access materials for matrix cleanup. Electrophoresis. 31(13). 2279–2288. 21 indexed citations
20.
Rodríguez‐Gonzalo, Encarnación, Diego García‐Gómez, Eliseo Herrero‐Hernández, & R. Carabias-Martı́nez. (2010). Automated sample treatment with the injection of large sample volumes for the determination of contaminants and metabolites in urine. Journal of Separation Science. 33(15). 2240–2249. 7 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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