Sheema Khan

3.8k total citations
74 papers, 3.0k citations indexed

About

Sheema Khan is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Sheema Khan has authored 74 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 22 papers in Oncology and 17 papers in Cancer Research. Recurrent topics in Sheema Khan's work include Nanoparticle-Based Drug Delivery (15 papers), Pancreatic and Hepatic Oncology Research (14 papers) and MicroRNA in disease regulation (11 papers). Sheema Khan is often cited by papers focused on Nanoparticle-Based Drug Delivery (15 papers), Pancreatic and Hepatic Oncology Research (14 papers) and MicroRNA in disease regulation (11 papers). Sheema Khan collaborates with scholars based in United States, India and Saudi Arabia. Sheema Khan's co-authors include Meena Jaggi, Subhash C. Chauhan, Murali M. Yallapu, Aditya Ganju, Stephen W. Behrman, Bilal Bin Hafeez, Neeraj Chauhan, Mara C. Ebeling, Nadeem Zafar and Diane M. Maher and has published in prestigious journals such as Gastroenterology, PLoS ONE and Biomaterials.

In The Last Decade

Sheema Khan

71 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheema Khan United States 28 1.5k 632 593 584 448 74 3.0k
Ahmed M. Al‐Abd Egypt 29 1.1k 0.7× 579 0.9× 519 0.9× 224 0.4× 528 1.2× 86 3.0k
Shu‐Fen Peng Taiwan 31 1.8k 1.2× 537 0.8× 279 0.5× 307 0.5× 270 0.6× 109 3.4k
Amir Abbas Momtazi‐Borojeni Iran 38 1.6k 1.0× 345 0.5× 654 1.1× 586 1.0× 312 0.7× 126 4.0k
V. Badireenath Konkimalla India 24 1.2k 0.8× 778 1.2× 367 0.6× 203 0.3× 488 1.1× 80 3.2k
Ling Zhao China 32 1.0k 0.7× 659 1.0× 340 0.6× 207 0.4× 472 1.1× 95 2.7k
Yan Chen China 37 1.8k 1.2× 1.1k 1.7× 328 0.6× 470 0.8× 1.5k 3.3× 164 4.5k
Chanakya Nath Kundu India 38 2.1k 1.4× 282 0.4× 990 1.7× 436 0.7× 385 0.9× 124 4.1k
Yao Fu China 36 1.9k 1.2× 1.1k 1.8× 378 0.6× 531 0.9× 866 1.9× 161 4.2k
Huanjie Yang China 32 2.0k 1.3× 254 0.4× 721 1.2× 505 0.9× 420 0.9× 57 3.8k
Nasser Samadi Iran 34 1.6k 1.1× 333 0.5× 412 0.7× 502 0.9× 247 0.6× 98 2.9k

Countries citing papers authored by Sheema Khan

Since Specialization
Citations

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

Fields of papers citing papers by Sheema Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheema Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Sheema Khan. A scholar is included among the top collaborators of Sheema 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 Sheema Khan. Sheema 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.
Khan, Sheema, et al.. (2024). FREQUENCY OF OBESITY IN PATIENTS WITH TYPE 2 DIABETES MELLITUS. 32(2). 126–130.
2.
Kashyap, Vivek K., Prashanth K.B. Nagesh, Andrew E. Massey, et al.. (2024). Curcumin attenuates smoking and drinking activated NF-κB/IL-6 inflammatory signaling axis in cervical cancer. Cancer Cell International. 24(1). 343–343. 6 indexed citations
3.
Malik, Shabnam, Mohammed Sikander, Mohd Wahid, et al.. (2024). Deciphering cellular and molecular mechanism of MUC13 mucin involved in cancer cell plasticity and drug resistance. Cancer and Metastasis Reviews. 43(3). 981–999. 5 indexed citations
4.
Dhasmana, Anupam, Sheema Khan, Farrukh Afaq, et al.. (2023). An integrated computational biology approach defines the crucial role of TRIP13 in pancreatic cancer. Computational and Structural Biotechnology Journal. 21. 5765–5775. 2 indexed citations
5.
Khan, Sheema, et al.. (2023). An In-depth Examination of Validity Assessment: Exploring Diverse Methodologies and Dimensions of Validity in Social Research Studies. Asian Journal of Agricultural Extension Economics & Sociology. 41(10). 772–782. 2 indexed citations
6.
Chaib, Mehdi, Bilal Bin Hafeez, Deidre Daria, et al.. (2022). Reprogramming of pancreatic adenocarcinoma immunosurveillance by a microbial probiotic siderophore. Communications Biology. 5(1). 1181–1181. 12 indexed citations
7.
Nagesh, Prashanth K.B., Pallabita Chowdhury, Elham Hatami, et al.. (2018). miRNA-205 Nanoformulation Sensitizes Prostate Cancer Cells to Chemotherapy. Cancers. 10(9). 289–289. 43 indexed citations
8.
Nagesh, Prashanth K.B., Elham Hatami, Pallabita Chowdhury, et al.. (2018). Tannic Acid Induces Endoplasmic Reticulum Stress-Mediated Apoptosis in Prostate Cancer. Cancers. 10(3). 68–68. 52 indexed citations
9.
Khan, Sheema, Mohammed Sikander, Mara C. Ebeling, et al.. (2016). MUC13 interaction with receptor tyrosine kinase HER2 drives pancreatic ductal adenocarcinoma progression. Oncogene. 36(4). 491–500. 26 indexed citations
10.
Setua, Saini, Sheema Khan, Murali M. Yallapu, et al.. (2016). Restitution of Tumor Suppressor MicroRNA-145 Using Magnetic Nanoformulation for Pancreatic Cancer Therapy. Journal of Gastrointestinal Surgery. 21(1). 94–105. 37 indexed citations
11.
Khan, Sheema, Mara C. Ebeling, Neeraj Chauhan, et al.. (2015). Ormeloxifene Suppresses Desmoplasia and Enhances Sensitivity of Gemcitabine in Pancreatic Cancer. Cancer Research. 75(11). 2292–2304. 61 indexed citations
12.
Yallapu, Murali M., Neeraj Chauhan, Shadi F. Othman, et al.. (2015). Implications of protein corona on physico-chemical and biological properties of magnetic nanoparticles. Biomaterials. 46. 1–12. 147 indexed citations
13.
Khan, Sheema, Neeraj Chauhan, Murali M. Yallapu, et al.. (2015). Nanoparticle formulation of ormeloxifene for pancreatic cancer. Biomaterials. 53. 731–743. 36 indexed citations
14.
Khan, Sheema, Meena Jaggi, & Subhash C. Chauhan. (2015). Revisiting stroma in pancreatic cancer. Oncoscience. 2(10). 819–820. 3 indexed citations
15.
Maher, Diane M., Sheema Khan, Mara C. Ebeling, et al.. (2014). Ormeloxifene efficiently inhibits ovarian cancer growth. Cancer Letters. 356(2). 606–612. 24 indexed citations
16.
Yallapu, Murali M., Mara C. Ebeling, Sheema Khan, et al.. (2013). Novel Curcumin-Loaded Magnetic Nanoparticles for Pancreatic Cancer Treatment. Molecular Cancer Therapeutics. 12(8). 1471–1480. 104 indexed citations
17.
Khan, Sheema, Md Ansarullah, Deepak Kumar, Meena Jaggi, & Subhash C. Chauhan. (2013). Targeting microRNAs in Pancreatic Cancer: Microplayers in the Big Game. Cancer Research. 73(22). 6541–6547. 59 indexed citations
18.
Khan, Sheema, et al.. (2012). ROLE OF HIGH RESOLUTION COMPUTED TOMOGRAPHIC SCAN IN DIAGNOSIS OF INTERSTITIAL LUNG DISEASES IN LOCAL POPULATION. Journal of Postgraduate Medical Institute. 26(2). 1 indexed citations
19.
20.
Khan, Sheema, Bhahwal Ali Shah, Zahoor A. Wani, et al.. (2011). A cyano analogue of boswellic acid induces crosstalk between p53/PUMA/Bax and telomerase that stages the human papillomavirus type 18 positive HeLa cells to apoptotic death. European Journal of Pharmacology. 660(2-3). 241–248. 29 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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