Janet Piñero
- Molecular Biology top 2%
- Computational Theory and Mathematics top 0.5%
- Genetics top 5%
- Cancer Research top 5%
- Pharmacology top 0.5%
- Co-authors
- Laura I. FurlongFerrán SanzEmilio CentenoÁlex BravoNúria Queralt-RosiñachJordi Deu-PonsFrancesco RonzanoJuan Manuel Ramírez‐Anguita
- Topics
- Bioinformatics and Genomic Networks (29 papers)Computational Drug Discovery Methods (12 papers)Biomedical Text Mining and Ontologies (10 papers)
- Journals
- Nucleic Acids ResearchSHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- SpainNetherlandsUnited Kingdom
In The Last Decade
Janet Piñero
39 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Molecular Biology 3.5k
- Computational Theory and Mathematics 946
- Genetics 654
- Cancer Research 599
- Pharmacology 595
Countries citing papers authored by Janet Piñero
This map shows the geographic impact of Janet Piñero'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 Janet Piñero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janet Piñero more than expected).
Fields of papers citing papers by Janet Piñero
This network shows the impact of papers produced by Janet Piñero. 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 Janet Piñero. The network helps show where Janet Piñero may publish in the future.
Co-authorship network of co-authors of Janet Piñero
This figure shows the co-authorship network connecting the top 25 collaborators of Janet Piñero. A scholar is included among the top collaborators of Janet Piñero 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 Janet Piñero. Janet Piñero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 9 | |
| 7 | 9 | |
| 8 | 10 | |
| 9 | 11 | |
| 10 | The DisGeNET knowledge platform for disease genomics: 2019 updatebreakdown → | 1752 |
| 11 | 22 | |
| 12 | 31 | |
| 13 | 27 | |
| 14 | 37 | |
| 15 | Slim-o-matic: a Semi-Automated Way to Generate Gene Ontology Slims. | 1 |
| 16 | DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variantsbreakdown → | 1779 |
| 17 | 174 | |
| 18 | DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genesbreakdown → | 785 |
| 19 | 19 | |
| 20 | 10 |
About Janet Piñero
Janet Piñero is a scholar working on Computational Theory and Mathematics, Molecular Biology and Biological Psychiatry, having authored 42 papers that have together received 5.3k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (29 papers), Computational Drug Discovery Methods (12 papers) and Biomedical Text Mining and Ontologies (10 papers). The work is most often cited by research in Pharmacology (595 citations), Computational Theory and Mathematics (946 citations) and Biological Psychiatry (130 citations). Janet Piñero has collaborated with scholars based in Spain, Netherlands and United Kingdom. Frequent co-authors include Laura I. Furlong, Ferrán Sanz, Emilio Centeno, Álex Bravo, Núria Queralt-Rosiñach, Jordi Deu-Pons, Francesco Ronzano, Juan Manuel Ramírez‐Anguita, Alba Gutiérrez‐Sacristán and Javier Garcı́a-Garcı́a. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.
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.