Imran Khan

2.3k total citations
63 papers, 1.7k citations indexed

About

Imran Khan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Imran Khan has authored 63 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 15 papers in Pulmonary and Respiratory Medicine and 12 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Imran Khan's work include Laser Applications in Dentistry and Medicine (10 papers), Oral Health Pathology and Treatment (7 papers) and Natural product bioactivities and synthesis (6 papers). Imran Khan is often cited by papers focused on Laser Applications in Dentistry and Medicine (10 papers), Oral Health Pathology and Treatment (7 papers) and Natural product bioactivities and synthesis (6 papers). Imran Khan collaborates with scholars based in United States, India and Pakistan. Imran Khan's co-authors include Praveen Arany, Patricia S. Steeg, Paturu Kondaiah, Ila Pant, Akhil R. Chakravarty, Akhtar Hussain, Uttara Basu, Surrinder Koul, Payare L. Sangwan and Neeraj Kumar and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Imran Khan

61 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Imran Khan United States 26 630 331 291 278 260 63 1.7k
Minal Chaudhary India 20 442 0.7× 48 0.1× 167 0.6× 202 0.7× 381 1.5× 89 1.6k
Soo‐A Kim South Korea 28 1.2k 2.0× 47 0.1× 239 0.8× 228 0.8× 32 0.1× 87 2.2k
Yen‐Yun Wang Taiwan 22 540 0.9× 45 0.1× 200 0.7× 294 1.1× 191 0.7× 79 1.3k
Moshe Schaffer Germany 22 702 1.1× 330 1.0× 531 1.8× 360 1.3× 27 0.1× 63 2.1k
Yingjie Xu China 26 1.7k 2.8× 43 0.1× 165 0.6× 312 1.1× 57 0.2× 92 2.8k
S Takahashi Japan 23 616 1.0× 178 0.5× 143 0.5× 250 0.9× 20 0.1× 48 1.9k
Dorota Bartusik‐Aebisher Poland 22 401 0.6× 146 0.4× 604 2.1× 94 0.3× 22 0.1× 148 1.8k
Maliheh Paknejad Iran 18 339 0.5× 94 0.3× 104 0.4× 88 0.3× 16 0.1× 59 830
Lucas L. Colombo Argentina 23 810 1.3× 242 0.7× 153 0.5× 424 1.5× 9 0.0× 76 2.0k
Danyang Wang China 24 807 1.3× 66 0.2× 49 0.2× 95 0.3× 27 0.1× 62 1.4k

Countries citing papers authored by Imran Khan

Since Specialization
Citations

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

Fields of papers citing papers by Imran Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Imran Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Imran Khan. A scholar is included among the top collaborators of Imran Khan 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 Imran Khan. Imran Khan 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.
2.
Bunick, Christopher G., April W. Armstrong, Ayman Grada, et al.. (2025). The Epidemiology of Atopic Dermatitis among Adults and Adolescents with Alopecia Areata in the United States. Journal of Investigative Dermatology. 146(2). 365–373.e3. 1 indexed citations
3.
Mohan, Ganesh, Imran Khan, Malgorzata M. Kamocka, et al.. (2024). Quantification of Lymphangiogenesis in the Murine Lymphedema Tail Model Using Intravital Microscopy. Lymphatic Research and Biology. 22(3). 195–202. 2 indexed citations
4.
Çeli̇k, İsmail, et al.. (2024). Investigating Potential Cancer Therapeutics: Insight into Histone Deacetylases (HDACs) Inhibitions. Pharmaceuticals. 17(4). 444–444. 6 indexed citations
5.
Bezrookove, Vladimir, Imran Khan, Anukana Bhattacharjee, et al.. (2024). miR-876-3p is a tumor suppressor on 9p21 that is inactivated in melanoma and targets ERK. Journal of Translational Medicine. 22(1). 758–758. 1 indexed citations
6.
Khan, Imran, Brunilde Gril, Anurag N. Paranjape, et al.. (2023). Comparison of Three Transcytotic Pathways for Distribution to Brain Metastases of Breast Cancer. Molecular Cancer Therapeutics. 22(5). 646–658. 3 indexed citations
7.
Hunt, Allison L., Imran Khan, Sasha C. Makohon‐Moore, et al.. (2023). The murine metastatic microenvironment of experimental brain metastases of breast cancer differs by host age in vivo: a proteomic study. Clinical & Experimental Metastasis. 41(3). 229–249. 1 indexed citations
8.
Khan, Imran, Sana Aslam, Usman Ali Ashfaq, et al.. (2022). Synthesis of Novel N-Methylmorpholine-Substituted Benzimidazolium Salts as Potential α-Glucosidase Inhibitors. Molecules. 27(18). 6012–6012. 9 indexed citations
9.
Khan, Imran, Brunilde Gril, Ayuko Hoshino, et al.. (2022). Metastasis suppressor NME1 in exosomes or liposomes conveys motility and migration inhibition in breast cancer model systems. Clinical & Experimental Metastasis. 39(5). 815–831. 7 indexed citations
10.
Hassanein, Aladdin H., et al.. (2021). A Murine Tail Lymphedema Model. Journal of Visualized Experiments. 13 indexed citations
11.
Khan, Imran, et al.. (2021). MiRNA expression profiling and emergence of new prognostic signature for oral squamous cell carcinoma. Scientific Reports. 11(1). 7298–7298. 38 indexed citations
12.
Khan, Imran, Brunilde Gril, & Patricia S. Steeg. (2019). Metastasis Suppressors NME1 and NME2 Promote Dynamin 2 Oligomerization and Regulate Tumor Cell Endocytosis, Motility, and Metastasis. Cancer Research. 79(18). 4689–4702. 40 indexed citations
13.
Balla, Murali Mohan Sagar, et al.. (2017). In vitro characterization of CD133lo cancer stem cells in Retinoblastoma Y79 cell line. BMC Cancer. 17(1). 779–779. 26 indexed citations
14.
Khan, Imran & Praveen Arany. (2016). Photobiomodulation Therapy Promotes Expansion of Epithelial Colony Forming Units. Photomedicine and Laser Surgery. 34(11). 550–555. 26 indexed citations
15.
16.
Khan, Imran & Praveen Arany. (2015). Biophysical Approaches for Oral Wound Healing: Emphasis on Photobiomodulation. Advances in Wound Care. 4(12). 724–737. 72 indexed citations
17.
Pant, Ila, et al.. (2015). Role of Areca Nut Induced TGF-β and Epithelial-Mesenchymal Interaction in the Pathogenesis of Oral Submucous Fibrosis. PLoS ONE. 10(6). e0129252–e0129252. 54 indexed citations
18.
Jamila, Nargis, Kooi Yeong Khaw, Vikneswaran Murugaiyah, et al.. (2014). Molecular docking studies andin vitrocholinesterase enzyme inhibitory activities of chemical constituents ofGarcinia hombroniana. Natural Product Research. 29(1). 86–90. 15 indexed citations
19.
Basu, Uttara, Imran Khan, Akhtar Hussain, Paturu Kondaiah, & Akhil R. Chakravarty. (2012). Photodynamic Effect in Near‐IR Light by a Photocytotoxic Iron(III) Cellular Imaging Agent. Angewandte Chemie International Edition. 51(11). 2658–2661. 119 indexed citations
20.
Khan, Imran, et al.. (2011). Role of TGF-beta beta and BMP7 in the pathogenesis of oral submucous fibrosis. NOT FOUND REPOSITORY (Indian Institute of Science Bangalore). 12 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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