Natalia Quinones‐Olvera
Impact in
- Endocrinology top 10%
- Molecular Biology top 10%
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- RNA Research and Splicing
Papers in
-
- Genomics and Phylogenetic Studies 4
- RNA and protein synthesis mechanisms 3
- RNA modifications and cancer 2
- Advanced biosensing and bioanalysis techniques 1
- Machine Learning in Bioinformatics 1
- Ecology 2
- Bacteriophages and microbial interactions 2
- Co-authors
- Joanna Argasinska (2 shared papers)Alex Bateman (2 shared papers)ROBERT FINN (2 shared papers)Eric P. Nawrocki (2 shared papers)Ioanna Kalvari (2 shared papers)Anton I. Petrov (2 shared papers)Sean R. Eddy (1 shared paper)Elena Rivas (1 shared paper)
- Journals
- Nature Methods (1 paper)PLoS Pathogens (1 paper)Science (1 paper)Nature Communications (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Natalia Quinones‐Olvera
8 papers receiving 991 citations
Natalia Quinones‐Olvera's Hit Papers
Peers
Comparison fields: 5 of 96
- Endocrinology 68
- Molecular Biology 704
- Cancer Research 148
- Plant Science 271
- Ecology 185
Countries citing papers authored by Natalia Quinones‐Olvera
This map shows the geographic impact of Natalia Quinones‐Olvera'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 Natalia Quinones‐Olvera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalia Quinones‐Olvera more than expected).
Fields of papers citing papers by Natalia Quinones‐Olvera
This network shows the impact of papers produced by Natalia Quinones‐Olvera. 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 Natalia Quinones‐Olvera. The network helps show where Natalia Quinones‐Olvera may publish in the future.
Co-authors
The 25 scholars most cited alongside Natalia Quinones‐Olvera, 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 | Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families Hit paper breakdown → | 2017 | 639 |
| 2 | 2018 | 285 | |
| 3 | 2024 | 28 | |
| 4 | 2019 | 20 | |
| 5 | 2025 | 17 | |
| 6 | 2025 | 4 | |
| 7 | 2025 | 3 | |
| 8 | 2025 | 2 |
About Natalia Quinones‐Olvera
Natalia Quinones‐Olvera is a scholar working on Molecular Biology, Ecology, Microbiology, Artificial Intelligence and Molecular Medicine, having authored 8 papers that have together received 998 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (4 papers), RNA and protein synthesis mechanisms (3 papers), Bacteriophages and microbial interactions (2 papers), RNA modifications and cancer (2 papers), Microbial infections and disease research (2 papers), Advanced biosensing and bioanalysis techniques (1 paper), Machine Learning in Bioinformatics (1 paper) and Salmonella and Campylobacter epidemiology (1 paper). The work is most often cited by research in Endocrinology (68 citations), Molecular Biology (704 citations), Cancer Research (148 citations), Plant Science (271 citations) and Ecology (185 citations). Natalia Quinones‐Olvera has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Joanna Argasinska, Alex Bateman, ROBERT FINN, Eric P. Nawrocki, Ioanna Kalvari, Anton I. Petrov, Sean R. Eddy, Elena Rivas, Michael Baym and Siân V. Owen. Their work appears in journals such as Nature Methods, PLoS Pathogens, Science, Nature Communications 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.