Anwar Rayan

1.8k citations
52 papers · 1.4k · h-index 21

Impact in

Papers in

Anwar Rayan

52 papers receiving 1.4k citations

Peers

Anwar Rayan
Comparison fields: 5 of 129
  • Computational Theory and Mathematics 300
  • Biochemistry 103
  • Applied Microbiology and Biotechnology 26
  • Pharmacology 102
  • Toxicology 38
Replace Palesa Pamela Seele with:
Palesa Pamela Seele South Africa
Abhinav Grover India
Onat Kadioglu Germany
Ashok Sharma India
Rajnish Kumar India
Xiaojun Yao Macao
Lixia Sun China
Vinícius Gonçalves Maltarollo Brazil
Manish Tripathi India
Shopnil Akash Bangladesh
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Citations per field
00.5×10×14.5×
Palesa Pamela Seele · 1×
Citations per year

Countries citing papers authored by Anwar Rayan

Since Specialization
Citations

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

Fields of papers citing papers by Anwar Rayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017267
2 2011198
3 201773
4 201069
5 201946
6 200240
7 201738
8 202337
9 201736
10 200934
11 201930
12 200428
13 201827
14 201026
15 201926
16 202125
17 201923
18 201922
19 200921
20 202020

About Anwar Rayan

Anwar Rayan is a scholar working on Molecular Biology, Computational Theory and Mathematics, Food Science, Plant Science and Materials Chemistry, having authored 52 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (15 papers), Receptor Mechanisms and Signaling (6 papers), Essential Oils and Antimicrobial Activity (5 papers), Enzyme Structure and Function (4 papers), Protein Structure and Dynamics (4 papers), Oral microbiology and periodontitis research (4 papers), Chemical Synthesis and Analysis (4 papers) and Bacterial biofilms and quorum sensing (3 papers). The work is most often cited by research in Computational Theory and Mathematics (300 citations), Biochemistry (103 citations), Applied Microbiology and Biotechnology (26 citations), Pharmacology (102 citations) and Toxicology (38 citations). Anwar Rayan has collaborated with scholars based in Israel, Palestinian Territory and Lithuania. Frequent co-authors include Mizied Falah, Jamal Raiyn, Amiram Goldblum, Oleg Ursu, Tudor I. Oprea, Mahmoud Rayan, Saleh Abu‐Lafi, Meir Glick, Wajeeh Daher and David Marcus. Their work appears in journals such as Molecules, PLoS ONE, Inflammation Research, Molecular Informatics and Wiley Interdisciplinary Reviews Computational Molecular Science.

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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