Antonio Fabregat

21.2k total citations · 2 hit papers
15 papers, 2.9k citations indexed

About

Antonio Fabregat is a scholar working on Molecular Biology, Spectroscopy and Genetics. According to data from OpenAlex, Antonio Fabregat has authored 15 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Spectroscopy and 2 papers in Genetics. Recurrent topics in Antonio Fabregat's work include Bioinformatics and Genomic Networks (11 papers), Microbial Metabolic Engineering and Bioproduction (6 papers) and Advanced Proteomics Techniques and Applications (5 papers). Antonio Fabregat is often cited by papers focused on Bioinformatics and Genomic Networks (11 papers), Microbial Metabolic Engineering and Bioproduction (6 papers) and Advanced Proteomics Techniques and Applications (5 papers). Antonio Fabregat collaborates with scholars based in United Kingdom, Spain and United States. Antonio Fabregat's co-authors include Henning Hermjakob, Konstantinos Sidiropoulos, Guilherme Viteri, Johannes Griss, Peter D’Eustachio, Lincoln Stein, Juan Antonio Vizcaíno, Joseph Foster, Pablo Marín-García and Rui Wang and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Antonio Fabregat

15 papers receiving 2.9k citations

Hit Papers

The Proteomics Identifications (PRIDE) database and assoc... 2012 2026 2016 2021 2012 2017 500 1000 1.5k
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 Proteomics Identifications (PRIDE) database and associated tools: status in 2013
    2012 1.6k citations Juan Antonio Vizcaíno, Richard G. Côté et al. Nucleic Acids Research profile →
  2. Reactome pathway analysis: a high-performance in-memory approach
    2017 533 citations Antonio Fabregat, Konstantinos Sidiropoulos et al. BMC Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Antonio Fabregat United Kingdom 10 1.8k 453 334 269 260 15 2.9k
Songfeng Wu China 19 1.7k 0.9× 517 1.1× 246 0.7× 278 1.0× 238 0.9× 50 2.8k
Noemí del‐Toro United Kingdom 13 2.5k 1.3× 641 1.4× 333 1.0× 209 0.8× 230 0.9× 17 3.7k
Gerhard Mayer Germany 12 2.4k 1.3× 835 1.8× 304 0.9× 190 0.7× 219 0.8× 15 3.5k
Emanuele Alpi United Kingdom 11 1.6k 0.9× 493 1.1× 221 0.7× 242 0.9× 163 0.6× 14 2.3k
Tobias Ternent United Kingdom 8 2.6k 1.4× 731 1.6× 369 1.1× 241 0.9× 270 1.0× 9 3.9k
Linn Fagerberg Sweden 28 2.1k 1.1× 434 1.0× 294 0.9× 302 1.1× 249 1.0× 55 3.1k
David García‐Seisdedos Spain 10 2.6k 1.4× 431 1.0× 441 1.3× 292 1.1× 379 1.5× 16 4.2k
Sheenah M. Mische United States 16 1.8k 1.0× 341 0.8× 328 1.0× 187 0.7× 291 1.1× 34 2.9k
Yunping Zhu China 28 2.5k 1.4× 712 1.6× 402 1.2× 464 1.7× 451 1.7× 112 4.1k
Jingwen Bai China 5 2.7k 1.5× 416 0.9× 472 1.4× 257 1.0× 358 1.4× 6 4.4k

Countries citing papers authored by Antonio Fabregat

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Fabregat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonio Fabregat

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Fabregat. A scholar is included among the top collaborators of Antonio Fabregat 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 Antonio Fabregat. Antonio Fabregat 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.
Griss, Johannes, Guilherme Viteri, Konstantinos Sidiropoulos, et al.. (2020). ReactomeGSA - Efficient Multi-Omics Comparative Pathway Analysis. Molecular & Cellular Proteomics. 19(12). 2115–2125. 183 indexed citations
2.
Viteri, Guilherme, Lisa Matthews, Thawfeek Varusai, et al.. (2019). Reactome and ORCID—fine-grained credit attribution for community curation. Database. 2019. 9 indexed citations
3.
Fabregat, Antonio, Stefan Johansson, Pål R. Njølstad, et al.. (2019). PathwayMatcher: proteoform-centric network construction enables fine-granularity multiomics pathway mapping. GigaScience. 8(8). 3 indexed citations
4.
Fabregat, Antonio, Guilherme Viteri, Konstantinos Sidiropoulos, et al.. (2018). Reactome graph database: Efficient access to complex pathway data. PLoS Computational Biology. 14(1). e1005968–e1005968. 169 indexed citations
5.
Fabregat, Antonio, Konstantinos Sidiropoulos, Guilherme Viteri, et al.. (2017). Reactome pathway analysis: a high-performance in-memory approach. BMC Bioinformatics. 18(1). 142–142. 533 indexed citations breakdown →
6.
Fabregat, Antonio, Konstantinos Sidiropoulos, Guilherme Viteri, et al.. (2017). Reactome diagram viewer: data structures and strategies to boost performance. Bioinformatics. 34(7). 1208–1214. 124 indexed citations
7.
Sidiropoulos, Konstantinos, Guilherme Viteri, Cristoffer Sevilla, et al.. (2017). Reactome enhanced pathway visualization. Bioinformatics. 33(21). 3461–3467. 115 indexed citations
8.
Naithani, Sushma, Justin Preece, Peter D’Eustachio, et al.. (2016). Plant Reactome: a resource for plant pathways and comparative analysis. Nucleic Acids Research. 45(D1). D1029–D1039. 41 indexed citations
9.
Jupe, S, Antonio Fabregat, & Henning Hermjakob. (2015). Expression Data Analysis with Reactome. Current Protocols in Bioinformatics. 49(1). 8.20.1–8.20.9. 15 indexed citations
10.
Porras, Pablo, Margaret Duesbury, Antonio Fabregat, et al.. (2015). A visual review of the interactome of LRRK2: Using deep‐curated molecular interaction data to represent biology. PROTEOMICS. 15(8). 1390–1404. 34 indexed citations
11.
Foster, Joseph, Pablo Moreno, Antonio Fabregat, et al.. (2013). LipidHome: A Database of Theoretical Lipids Optimized for High Throughput Mass Spectrometry Lipidomics. PLoS ONE. 8(5). e61951–e61951. 60 indexed citations
12.
Vizcaíno, Juan Antonio, Richard G. Côté, Attila Csordás, et al.. (2012). The Proteomics Identifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Research. 41(D1). D1063–D1069. 1638 indexed citations breakdown →
13.
Coltell, Óscar, María Arregui, Antonio Fabregat, & Olga Portolés. (2008). La bioinformática en la práctica médica: Integración de datos biológicos y clínicos. Revista médica de Chile. 136(5). 645–52. 1 indexed citations
14.
Fabregat, Antonio, et al.. (2008). NutriGeneOntology: A Biomedical Ontology for Nutrigenomics Research. 9. 915–919. 1 indexed citations
15.
Fabregat, Antonio, Elisabet Barrera, María Arregui, et al.. (2008). BOGENVI: A Biomedical Ontology for Modelling Gene*Environment Interactions on Intermediate Phenotypes in Nutrigenomics Research. 9. 302–307. 1 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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