Ashraf Dada

29 papers receiving 911 citations

Peers

Ashraf Dada
Comparison fields: 5 of 99
  • Infectious Diseases 310
  • Modeling and Simulation 52
  • Urology 72
  • Immunology 186
  • Hematology 71
Replace Mathieu Surénaud with:
Mathieu Surénaud France
Arundhati Rao United States
Ramadan A. Ali United States
Dorothee Schwinge Germany
Tsvetoslav Georgiev Bulgaria
Lyn R. Frumkin United States
Elena Bazzigaluppi Italy
Hanan Guzner‐Gur Israel
İrfan Kuku Türkiye
Maria Suprun United States
Ashraf Dada relative to Mathieu Surénaud France Mathieu Surénaud's profile →
Citations per field
00.5×10×17.3×
Mathieu Surénaud · 1×
Citations per year

Countries citing papers authored by Ashraf Dada

Since Specialization
Citations

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

Fields of papers citing papers by Ashraf Dada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ashraf Dada, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ashraf Dada Line = papers co-authored together Ashraf Dada links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017188
2 2006109
3 2006107
4 201694
5 200692
6 200767
7 200462
8 200737
9 200435
10 200629
11 200626
12 200717
13 202111
14 20138
15 20078
16 20218
17 20236
18 20216
19 20225
20 20234

About Ashraf Dada

Ashraf Dada is a scholar working on Infectious Diseases, Surgery, Molecular Biology, Hematology and Physiology, having authored 30 papers that have together received 931 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (12 papers), COVID-19 Clinical Research Studies (10 papers), SARS-CoV-2 detection and testing (6 papers), Cholesterol and Lipid Metabolism (5 papers), Blood transfusion and management (2 papers), Clinical Laboratory Practices and Quality Control (2 papers), Hematopoietic Stem Cell Transplantation (2 papers) and Caveolin-1 and cellular processes (2 papers). The work is most often cited by research in Infectious Diseases (310 citations), Modeling and Simulation (52 citations), Urology (72 citations), Immunology (186 citations) and Hematology (71 citations). Ashraf Dada has collaborated with scholars based in Saudi Arabia, Germany and United States. Frequent co-authors include Gerd Schmitz, Alfred Boettcher, Stefan Barlage, Abeer N. Alshukairi, Waleed Ahmed, Imran Khalid, Stanley Perlman, M. Christgau, Gottfried Schmalz and Christa Buechler. Their work appears in journals such as Journal of Infection and Public Health, Cytometry Part A, Scientific Reports, Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease and Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids.

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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