Safa Daoud

24 papers receiving 414 citations

Peers

Safa Daoud
Comparison fields: 5 of 100
  • Endocrine and Autonomic Systems 86
  • Drug Discovery 2
  • Toxicology 13
  • Computational Theory and Mathematics 59
  • Applied Microbiology and Biotechnology 6
Replace Li‐Qiang Sun with:
Li‐Qiang Sun United States
Katrin Fischer Germany
Abhishek Gour India
Noriyuki Okudaira Japan
Athar Husain India
Guorong Jiang China
V. Parthasarathy India
Kamel Metwally Egypt
Guru R. Valicherla India
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Citations per year

Countries citing papers authored by Safa Daoud

Since Specialization
Citations

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

Fields of papers citing papers by Safa Daoud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Safa 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 Safa Daoud Line = papers co-authored together Safa Daoud links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021146
2 202086
3 202244
4 202026
5 202222
6 202015
7 202213
8 202212
9 20227
10 20227
11 20216
12 20245
13 20255
14
Determination of Antimicrobial Drug Resistance among Bacterial Isolates in Two Hospitals of Baghdad
20204
15 20204
16 20234
17
Preparation, Physicochemical Characterization and Biological Evaluation of some Hesperidin Metal Complexes.
20143
18 20223
19 20243
20 20242

About Safa Daoud

Safa Daoud is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Oncology and Infectious Diseases, having authored 25 papers that have together received 421 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Synthesis and biological activity (3 papers), Phytochemicals and Antioxidant Activities (2 papers), Pneumonia and Respiratory Infections (2 papers), Chemical Synthesis and Analysis (2 papers), Bioactive Compounds and Antitumor Agents (2 papers), Tuberculosis Research and Epidemiology (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (86 citations), Drug Discovery (2 citations), Toxicology (13 citations), Computational Theory and Mathematics (59 citations) and Applied Microbiology and Biotechnology (6 citations). Safa Daoud has collaborated with scholars based in Jordan, United Kingdom and Pakistan. Frequent co-authors include Wamidh H. Talib, Asma Ismail Mahmod, Ahmad R. Alsayed, Alaa Abuawad, Mutasem O. Taha, Izzeddin Alsalahat, Lina A. Dahabiyeh, Lina T. Al Kury, Ma’mon M. Hatmal and Mohammed Al Maqbali. Their work appears in journals such as Molecular Informatics, Molecules, Journal of Molecular Graphics and Modelling, Acta Pharmaceutica and Molecular Diversity.

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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