Sarah ElShal
Impact in
Papers in
-
- Bioinformatics and Genomic Networks 5
- Machine Learning in Bioinformatics 3
- Gene expression and cancer classification 3
- Genomics and Phylogenetic Studies 2
- Biomedical Text Mining and Ontologies 2
- Genetics, Bioinformatics, and Biomedical Research 1
- Ecology 1
- Co-authors
- Yves Moreau (6 shared papers)Léon-Charles Tranchevent (2 shared papers)Amin Ardeshirdavani (2 shared papers)Didier Auboeuf (1 shared paper)Jan Aerts (1 shared paper)Jesse Davis (2 shared papers)Alejandro Sifrim (1 shared paper)Pooya Zakeri (3 shared papers)
- Journals
- Nucleic Acids Research (2 papers)Drug Safety (1 paper)Bioinformatics (1 paper)Faculty of 1000 Research Ltd (1 paper)Lirias (KU Leuven) (3 papers)
- Partner nations
- BelgiumFranceUnited States
In The Last Decade
Sarah ElShal
8 papers receiving 168 citations
Peers
Comparison fields: 5 of 69
- Health Informatics 7
- Toxicology 9
- Molecular Biology 125
- Computational Mathematics 1
- Genetics 32
Countries citing papers authored by Sarah ElShal
This map shows the geographic impact of Sarah ElShal'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 Sarah ElShal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sarah ElShal more than expected).
Fields of papers citing papers by Sarah ElShal
This network shows the impact of papers produced by Sarah ElShal. 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 Sarah ElShal. The network helps show where Sarah ElShal may publish in the future.
Co-authors
The 10 scholars most cited alongside Sarah ElShal, 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 | 2016 | 72 | |
| 2 | 2015 | 47 | |
| 3 | 2018 | 22 | |
| 4 | 2022 | 20 | |
| 5 | 2015 | 6 | |
| 6 | 2015 | 3 | |
| 7 | 2016 | 2 | |
| 8 | Gene Prioritization through Bayesian matrix factorization | 2015 | 1 |
About Sarah ElShal
Sarah ElShal is a scholar working on Molecular Biology, Ecology, Toxicology, Artificial Intelligence and Safety Research, having authored 8 papers that have together received 173 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Machine Learning in Bioinformatics (3 papers), Gene expression and cancer classification (3 papers), Genomics and Phylogenetic Studies (2 papers), Biomedical Text Mining and Ontologies (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Advanced Text Analysis Techniques (1 paper) and Pharmacovigilance and Adverse Drug Reactions (1 paper). The work is most often cited by research in Health Informatics (7 citations), Toxicology (9 citations), Molecular Biology (125 citations), Computational Mathematics (1 citation) and Genetics (32 citations). Sarah ElShal has collaborated with scholars based in Belgium, France and United States. Frequent co-authors include Yves Moreau, Léon-Charles Tranchevent, Amin Ardeshirdavani, Didier Auboeuf, Jan Aerts, Jesse Davis, Alejandro Sifrim, Pooya Zakeri, Ádám Arany and Jaak Simm. Their work appears in journals such as Nucleic Acids Research, Drug Safety, Bioinformatics, Faculty of 1000 Research Ltd and Lirias (KU Leuven).
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.