Danish Iqbal

2.2k total citations
73 papers, 1.5k citations indexed

About

Danish Iqbal is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Danish Iqbal has authored 73 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 13 papers in Pharmacology. Recurrent topics in Danish Iqbal's work include Computational Drug Discovery Methods (14 papers), Cholinesterase and Neurodegenerative Diseases (11 papers) and Plant biochemistry and biosynthesis (7 papers). Danish Iqbal is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Cholinesterase and Neurodegenerative Diseases (11 papers) and Plant biochemistry and biosynthesis (7 papers). Danish Iqbal collaborates with scholars based in Saudi Arabia, India and United States. Danish Iqbal's co-authors include M. Salman Khan, Saheem Ahmad, Sahir Sultan Alvi, Adnan Sarfraz, Saeed Banawas, Niraj Kumar Jha, Rajiv Dutta, Nabeel Ahmad, Bader Alshehri and Shreesh Ojha and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Chemical Communications.

In The Last Decade

Danish Iqbal

72 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danish Iqbal Saudi Arabia 23 426 309 216 199 171 73 1.5k
Jingjing Wu China 27 918 2.2× 184 0.6× 181 0.8× 133 0.7× 112 0.7× 98 2.2k
Thiyagarajan Ramesh Saudi Arabia 23 567 1.3× 238 0.8× 141 0.7× 211 1.1× 42 0.2× 92 1.8k
M. Yasmin Begum Saudi Arabia 22 396 0.9× 231 0.7× 105 0.5× 150 0.8× 70 0.4× 102 1.5k
Md. Abul Barkat Saudi Arabia 26 456 1.1× 172 0.6× 123 0.6× 180 0.9× 50 0.3× 75 1.6k
Mohd Farhan Saudi Arabia 27 564 1.3× 221 0.7× 97 0.4× 136 0.7× 56 0.3× 88 1.9k
Li Ren China 21 592 1.4× 293 0.9× 184 0.9× 266 1.3× 43 0.3× 87 1.7k
Fedora Grande Italy 27 980 2.3× 195 0.6× 150 0.7× 161 0.8× 194 1.1× 92 2.7k
Mehrnaz Mehrabani Iran 25 484 1.1× 92 0.3× 110 0.5× 169 0.8× 68 0.4× 84 1.6k
Sankarganesh Arunachalam India 19 448 1.1× 225 0.7× 79 0.4× 137 0.7× 47 0.3× 46 1.4k
Manoj Kumar India 21 599 1.4× 115 0.4× 203 0.9× 238 1.2× 48 0.3× 85 1.7k

Countries citing papers authored by Danish Iqbal

Since Specialization
Citations

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

Fields of papers citing papers by Danish Iqbal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danish Iqbal

This figure shows the co-authorship network connecting the top 25 collaborators of Danish Iqbal. A scholar is included among the top collaborators of Danish Iqbal 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 Danish Iqbal. Danish Iqbal 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
1.
Almutary, Abdulmajeed G., M. Yasmin Begum, Saurabh Gupta, et al.. (2024). Inflammatory signaling pathways in Alzheimer's disease: Mechanistic insights and possible therapeutic interventions. Ageing Research Reviews. 104. 102548–102548. 6 indexed citations
2.
Chauhan, Payal, Sumel Ashique, M. Arockia Babu, et al.. (2024). Mechanistic insights into the potential role of dietary polyphenols and their nanoformulation in the management of Alzheimer’s disease. Biomedicine & Pharmacotherapy. 174. 116376–116376. 20 indexed citations
3.
Vashisth, Kshitij, Shivani Sharma, Shampa Ghosh, et al.. (2024). Immunotherapy in Alzheimer’s Disease: Current Status and Future Directions. Journal of Alzheimer s Disease. 101(s1). S23–S39. 5 indexed citations
4.
Iqbal, Danish, Md Tabish Rehman, Mohamed F. Alajmi, et al.. (2023). Multitargeted Virtual Screening and Molecular Simulation of Natural Product-like Compounds against GSK3β, NMDA-Receptor, and BACE-1 for the Management of Alzheimer’s Disease. Pharmaceuticals. 16(4). 622–622. 9 indexed citations
5.
Iqbal, Danish, Mohammed Alsaweed, Qazi Mohammad Sajid Jamal, et al.. (2023). Pharmacophore-Based Screening, Molecular Docking, and Dynamic Simulation of Fungal Metabolites as Inhibitors of Multi-Targets in Neurodegenerative Disorders. Biomolecules. 13(11). 1613–1613. 12 indexed citations
6.
Rehman, Bushra, et al.. (2023). Phytochemical and Pharmacological Investigation of Lespedesea Gerardiana. VIII(IV). 23–33. 1 indexed citations
10.
Iqbal, Danish, Syed Mohd Danish Rizvi, Md Tabish Rehman, et al.. (2022). Soyasapogenol-B as a Potential Multitarget Therapeutic Agent for Neurodegenerative Disorders: Molecular Docking and Dynamics Study. Entropy. 24(5). 593–593. 18 indexed citations
11.
Hussain, Talib, Misbahuddin M. Rafeeq, El‐Sayed Khafagy, et al.. (2022). Oleuropein as a Potent Compound against Neurological Complications Linked with COVID-19: A Computational Biology Approach. Entropy. 24(7). 881–881. 6 indexed citations
12.
Iqbal, Danish, et al.. (2022). CRISPR/SpCas9-mediated KO of epigenetically active MORC proteins increases barley resistance to Bipolaris spot blotch and Fusarium root rot. Journal of Plant Diseases and Protection. 129(4). 1005–1011. 4 indexed citations
13.
Jahan, Sadaf, Arif Jamal Siddiqui, Danish Iqbal, et al.. (2022). Nobiletin Ameliorates Cellular Damage and Stress Response and Restores Neuronal Identity Altered by Sodium Arsenate Exposure in Human iPSCs-Derived hNPCs. Pharmaceuticals. 15(5). 593–593. 19 indexed citations
14.
Moin, Afrasim, Bader Huwaimel, Ahmed Alobaida, et al.. (2022). Dithymoquinone Analogues as Potential Candidate(s) for Neurological Manifestation Associated with COVID-19: A Therapeutic Strategy for Neuro-COVID. Life. 12(7). 1076–1076. 3 indexed citations
15.
Das, Sabya Sachi, Rahul Bhattacharjee, Asma Perveen, et al.. (2022). Molecular Insights into Therapeutic Potentials of Hybrid Compounds Targeting Alzheimer’s Disease. Molecular Neurobiology. 59(6). 3512–3528. 28 indexed citations
16.
Bhattacharjee, Rahul, Sabya Sachi Das, Sumira Malik, et al.. (2022). Mechanistic role of HPV-associated early proteins in cervical cancer: Molecular pathways and targeted therapeutic strategies. Critical Reviews in Oncology/Hematology. 174. 103675–103675. 109 indexed citations
17.
Iqbal, Danish, M. Salman Khan, Md Tabish Rehman, et al.. (2021). Exploring the Binding Pattern of Geraniol with Acetylcholinesterase through In Silico Docking, Molecular Dynamics Simulation, and In Vitro Enzyme Inhibition Kinetics Studies. Cells. 10(12). 3533–3533. 22 indexed citations
18.
Iqbal, Danish, Md Tabish Rehman, Abdulaziz Bin Dukhyil, et al.. (2021). High-Throughput Screening and Molecular Dynamics Simulation of Natural Product-like Compounds against Alzheimer’s Disease through Multitarget Approach. Pharmaceuticals. 14(9). 937–937. 46 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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