Sayed S. Daoud

943 citations
38 papers · 771 · h-index 17

Impact in

  • Oncology top 10%
    • Cancer-related Molecular Pathways
    • Lung Cancer Research Studies
  • Hepatology top 10%

Papers in

    • Cancer therapeutics and mechanisms 9
    • Cancer-related Molecular Pathways 10
    • Cancer Treatment and Pharmacology 2

Sayed S. Daoud

38 papers receiving 749 citations

Peers

Sayed S. Daoud
Comparison fields: 5 of 97
  • Oncology 294
  • Hepatology 55
  • Molecular Biology 459
  • Toxicology 22
  • Cancer Research 94
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Citations per year

Countries citing papers authored by Sayed S. Daoud

Since Specialization
Citations

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

Fields of papers citing papers by Sayed S. Daoud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sayed S. Daoud. 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 Sayed S. Daoud. The network helps show where Sayed S. Daoud may publish in the future.

Co-authors

The 25 scholars most cited alongside Sayed S. Daoud, 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 Sayed S. Daoud Line = papers co-authored together Sayed S. Daoud links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999105
2
Impact of p53 knockout and topotecan treatment on gene expression profiles in human colon carcinoma cells: a pharmacogenomic study.
200368
3 200551
4 201950
5 200039
6 199539
7 201334
8 198733
9 200631
10 201731
11 199730
12 201324
13 198924
14 199223
15 201121
16
Modulation of doxorubicin resistance by valinomycin (NSC 122023) and liposomal valinomycin in Chinese hamster ovary cells.
198920
17
Reduced toxicity and enhanced antitumor effects in mice of the ionophoric drug valinomycin when incorporated in liposomes.
198616
18 198715
19 199015
20 199614

About Sayed S. Daoud

Sayed S. Daoud is a scholar working on Molecular Biology, Oncology, Epidemiology, Hepatology and Biomaterials, having authored 38 papers that have together received 771 indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (10 papers), Cancer therapeutics and mechanisms (9 papers), Hepatitis C virus research (6 papers), Liver Disease Diagnosis and Treatment (6 papers), Nanoparticle-Based Drug Delivery (4 papers), Hepatitis B Virus Studies (4 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Oncology (294 citations), Hepatology (55 citations), Molecular Biology (459 citations), Toxicology (22 citations) and Cancer Research (94 citations). Sayed S. Daoud has collaborated with scholars based in United States, Egypt and Canada. Frequent co-authors include R. L. Juliano, Safia Wasi, Matthew M. Yeh, Dustin E. Bosch, Yves Pommier, Abdur Rehman, Beppino C. Giovanella, Kyunghee Lee, Xiaoting Tang and James E. Bruce. Their work appears in journals such as Anti-Cancer Drugs, Cancer Chemotherapy and Pharmacology, International Journal of Oncology, Biochemical and Biophysical Research Communications and Cancer Research.

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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