Fátima Al‐Shahrour
- Hematology top 0.5%
- Acute Myeloid Leukemia Research 15
- Genetics top 0.5%
- Myeloproliferative Neoplasms: Diagnosis and Treatment 10
- Molecular Biology top 2%
- Bioinformatics and Genomic Networks 25
- Gene expression and cancer classification 21
- Genomics and Chromatin Dynamics 8
- Biomedical Text Mining and Ontologies 7
- Cancer Research top 2%
- Cancer Genomics and Diagnostics 17
- Aging top 5%
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- Cancer Immunotherapy and Biomarkers 6
- Co-authors
- Joaquı́n DopazoRamón Díaz‐UriartePablo MínguezBenjamin L. EbertDavid MontanerLucía CondeJuan M. VaquerizasJoaquín Tárraga
- Cited by
- HematologyGeneticsMolecular Biology
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Fátima Al‐Shahrour
99 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Hematology 1.5k
- Genetics 1.2k
- Molecular Biology 3.9k
- Cancer Research 837
- Aging 70
Countries citing papers authored by Fátima Al‐Shahrour
This map shows the geographic impact of Fátima Al‐Shahrour'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 Fátima Al‐Shahrour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fátima Al‐Shahrour more than expected).
Fields of papers citing papers by Fátima Al‐Shahrour
This network shows the impact of papers produced by Fátima Al‐Shahrour. 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 Fátima Al‐Shahrour. The network helps show where Fátima Al‐Shahrour may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fátima Al‐Shahrour, 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 | 2024 | 9 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 13 | |
| 5 | 2022 | 19 | |
| 6 | 2021 | 15 | |
| 7 | 2021 | 5 | |
| 8 | 2021 | 102 | |
| 9 | 2020 | 2 | |
| 10 | 2020 | 35 | |
| 11 | 2019 | 5 | |
| 12 | 2018 | 60 | |
| 13 | 2017 | 74 | |
| 14 | 2016 | 189 | |
| 15 | 2015 | 103 | |
| 16 | 2014 | 110 | |
| 17 | 2014 | 107 | |
| 18 | 2013 | 35 | |
| 19 | 2012 | 31 | |
| 20 | 2011 | 45 |
About Fátima Al‐Shahrour
Fátima Al‐Shahrour is a scholar working on Hematology, Cancer Research and Genetics, having authored 100 papers that have together received 6.4k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (25 papers), Gene expression and cancer classification (21 papers), Cancer Genomics and Diagnostics (17 papers), Acute Myeloid Leukemia Research (15 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (10 papers), Genomics and Chromatin Dynamics (8 papers), Biomedical Text Mining and Ontologies (7 papers) and Cancer Immunotherapy and Biomarkers (6 papers). The work is most often cited by research in Hematology (1.5k citations), Genetics (1.2k citations) and Molecular Biology (3.9k citations). Fátima Al‐Shahrour has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Joaquı́n Dopazo, Ramón Díaz‐Uriarte, Pablo Mínguez, Benjamin L. Ebert, David Montaner, Lucía Conde, Juan M. Vaquerizas, Joaquín Tárraga, Eva Alloza and Ignacio Medina. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.