Khattab Al-Khafaji

930 total citations
32 papers, 648 citations indexed

About

Khattab Al-Khafaji is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Khattab Al-Khafaji has authored 32 papers receiving a total of 648 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 6 papers in Pharmacology. Recurrent topics in Khattab Al-Khafaji's work include Computational Drug Discovery Methods (8 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Protein Structure and Dynamics (3 papers). Khattab Al-Khafaji is often cited by papers focused on Computational Drug Discovery Methods (8 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Protein Structure and Dynamics (3 papers). Khattab Al-Khafaji collaborates with scholars based in Türkiye, Iraq and Bangladesh. Khattab Al-Khafaji's co-authors include Tuğba Taşkın‐Tok, Md. Oliullah Rafi, Md. Shahedur Rahman, Samir Abbas Ali Noma, Muhammad Torequl Islam, Burhan Ateş, Amit Kumar Das, Rajib Hossain, Md. Anowar Khasru Parvez and Md Almujaddade Alfasane and has published in prestigious journals such as SHILAP Revista de lepidopterología, Molecules and Life Sciences.

In The Last Decade

Khattab Al-Khafaji

31 papers receiving 639 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Khattab Al-Khafaji Türkiye 15 263 206 125 116 78 32 648
Kiran Bharat Lokhande India 16 289 1.1× 191 0.9× 111 0.9× 94 0.8× 66 0.8× 62 653
Arun Bahadur Gurung India 15 293 1.1× 293 1.4× 145 1.2× 178 1.5× 94 1.2× 46 749
Guanghao Zhu China 12 225 0.9× 186 0.9× 108 0.9× 110 0.9× 87 1.1× 49 608
Sisir Nandi India 15 290 1.1× 242 1.2× 228 1.8× 86 0.7× 45 0.6× 98 829
Thirumurthy Madhavan India 13 289 1.1× 193 0.9× 96 0.8× 67 0.6× 80 1.0× 72 694
Sajda Ashraf Pakistan 13 296 1.1× 261 1.3× 272 2.2× 172 1.5× 51 0.7× 52 801
Rohan Patil India 3 221 0.8× 159 0.8× 105 0.8× 41 0.4× 56 0.7× 10 519
Temitope Isaac Adelusi Nigeria 16 427 1.6× 218 1.1× 166 1.3× 48 0.4× 64 0.8× 45 851
Kumari Sunita Prajapati India 15 353 1.3× 183 0.9× 75 0.6× 91 0.8× 55 0.7× 37 716
Sunhye Hong South Korea 10 355 1.3× 279 1.4× 126 1.0× 48 0.4× 75 1.0× 13 836

Countries citing papers authored by Khattab Al-Khafaji

Since Specialization
Citations

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

Fields of papers citing papers by Khattab Al-Khafaji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khattab Al-Khafaji. 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 Khattab Al-Khafaji. The network helps show where Khattab Al-Khafaji may publish in the future.

Co-authorship network of co-authors of Khattab Al-Khafaji

This figure shows the co-authorship network connecting the top 25 collaborators of Khattab Al-Khafaji. A scholar is included among the top collaborators of Khattab Al-Khafaji based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Khattab Al-Khafaji. Khattab Al-Khafaji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Paul, Priyanka, et al.. (2024). Investigating the potent TOPO IIα inhibitors in breast cancer through the study of computational drug discovery research approaches. Molecular Diversity. 29(1). 655–670. 3 indexed citations
4.
Al-Khafaji, Khattab, et al.. (2023). New tamoxifen analogs for breast cancer therapy: synthesis, aromatase inhibition and in silico studies. Journal of Biomolecular Structure and Dynamics. 41(22). 12798–12807. 2 indexed citations
5.
Migas, Piotr, Mirosława Krauze‐Baranowska, Sadin Özdemir, et al.. (2023). HPLC-DAD-MS Characterization, Antioxidant Activity, α-amylase Inhibition, Molecular Docking, and ADMET of Flavonoids from Fenugreek Seeds. Molecules. 28(23). 7798–7798. 7 indexed citations
6.
Rafi, Md. Oliullah, et al.. (2023). A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae. Network Modeling Analysis in Health Informatics and Bioinformatics. 12(1). 21–21. 11 indexed citations
7.
Al-Khafaji, Khattab, Abdulcelil Yüzer, Serap Yalın, et al.. (2023). Superior photo-induced antibacterial/antibiofilm activities of ZnPcs/TiO2 and computational simulation studies. Journal of Materials Chemistry B. 11(27). 6361–6371. 4 indexed citations
8.
Saikat, Abu Saim Mohammad, et al.. (2022). Nature-Derived Compounds as Potential Bioactive Leads against CDK9-Induced Cancer: Computational and Network Pharmacology Approaches. Processes. 10(12). 2512–2512. 1 indexed citations
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Rafi, Md. Oliullah, et al.. (2022). Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods. RSC Advances. 12(7). 4288–4310. 41 indexed citations
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El-Mageed, H. R. Abd, Doaa A. Abdelrheem, Md. Oliullah Rafi, et al.. (2021). In Silico Evaluation of Different Flavonoids from Medicinal Plants for Their Potency against SARS-CoV-2. SHILAP Revista de lepidopterología. 1(3). 416–434. 16 indexed citations
12.
Hossain, Rajib, Muhammad Torequl Islam, Divya Jain, et al.. (2021). Amentoflavone, New Hope against SARS-CoV-2: An Outlook through its Scientific Records and an in silico Study. Pharmacognosy Research. 13(3). 149–157. 12 indexed citations
13.
Al-Khafaji, Khattab, et al.. (2021). Phytochemical constituents of Inula britannica as potential inhibitors of dihydrofolate reductase: A strategic approach against shigellosis. Journal of Biomolecular Structure and Dynamics. 40(22). 11932–11947. 9 indexed citations
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Rafi, Md. Oliullah, Khattab Al-Khafaji, Tuğba Taşkın‐Tok, & Md. Shahedur Rahman. (2020). Computer-based identification of potential compounds from Salviae miltiorrhizae against Neirisaral adhesion A regulatory protein. Journal of Biomolecular Structure and Dynamics. 40(10). 4301–4313. 14 indexed citations
16.
Al-Khafaji, Khattab, et al.. (2020). Using integrated computational approaches to identify safe and rapid treatment for SARS-CoV-2. Journal of Biomolecular Structure and Dynamics. 39(9). 3387–3395. 112 indexed citations
17.
Rafi, Md. Oliullah, Khattab Al-Khafaji, Tuğba Taşkın‐Tok, et al.. (2020). Combination of QSAR, molecular docking, molecular dynamic simulation and MM-PBSA: analogues of lopinavir and favipiravir as potential drug candidates against COVID-19. Journal of Biomolecular Structure and Dynamics. 40(8). 3711–3730. 52 indexed citations
18.
Al-Khafaji, Khattab, Tuğba Taşkın‐Tok, Zafer Çetin, et al.. (2020). Phycocyanine as a Potential Inhibitor of SARS-CoV-2-Spike/TMPRSS2 and SARS-CoV-2-RBD/ACE2 Interactions: An In silico Approach. 6(3). 1 indexed citations
19.
Al-Khafaji, Khattab & Tuğba Taşkın‐Tok. (2020). Molecular dynamics simulation, free energy landscape and binding free energy computations in exploration the anti-invasive activity of amygdalin against metastasis. Computer Methods and Programs in Biomedicine. 195. 105660–105660. 99 indexed citations
20.
Al-Khafaji, Khattab & Tuğba Taşkın‐Tok. (2020). Understanding the mechanism of amygdalin’s multifunctional anti-cancer action using computational approach. Journal of Biomolecular Structure and Dynamics. 39(5). 1600–1610. 15 indexed citations

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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