Iman Tavassoly

7.5k total citations
25 papers, 920 citations indexed

About

Iman Tavassoly is a scholar working on Molecular Biology, Cell Biology and Cancer Research. According to data from OpenAlex, Iman Tavassoly has authored 25 papers receiving a total of 920 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 6 papers in Cell Biology and 5 papers in Cancer Research. Recurrent topics in Iman Tavassoly's work include Endoplasmic Reticulum Stress and Disease (4 papers), Cancer Genomics and Diagnostics (4 papers) and Computational Drug Discovery Methods (3 papers). Iman Tavassoly is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (4 papers), Cancer Genomics and Diagnostics (4 papers) and Computational Drug Discovery Methods (3 papers). Iman Tavassoly collaborates with scholars based in United States, Iran and Canada. Iman Tavassoly's co-authors include Omid Tavassoly, Robert Clarke, Ravi Iyengar, Joseph Goldfarb, John J. Tyson, William T. Baumann, Farinaz Safavi, Anael Verdugo, Louis M. Weiner and Chun Chen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Nature reviews. Cancer.

In The Last Decade

Iman Tavassoly

24 papers receiving 910 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Iman Tavassoly United States 15 500 196 151 102 78 25 920
Ashutosh Mishra United States 19 888 1.8× 170 0.9× 167 1.1× 133 1.3× 150 1.9× 40 1.3k
Qixu Cai China 16 1.0k 2.0× 172 0.9× 196 1.3× 55 0.5× 81 1.0× 32 1.3k
Cuiping Pan China 12 654 1.3× 175 0.9× 91 0.6× 93 0.9× 67 0.9× 26 1.1k
Seung‐Wook Ryu South Korea 20 899 1.8× 201 1.0× 235 1.6× 175 1.7× 167 2.1× 39 1.6k
Rui Hao China 15 1.1k 2.1× 181 0.9× 224 1.5× 181 1.8× 167 2.1× 48 1.6k
Georg Tascher Germany 17 549 1.1× 130 0.7× 157 1.0× 94 0.9× 63 0.8× 35 945
Tejas Gandhi United States 12 1.3k 2.6× 136 0.7× 107 0.7× 122 1.2× 76 1.0× 26 1.8k
Maike Ahrens Germany 19 531 1.1× 67 0.3× 98 0.6× 115 1.1× 105 1.3× 31 908
Max Kotlyar Canada 20 1.1k 2.2× 150 0.8× 68 0.5× 114 1.1× 127 1.6× 49 1.6k

Countries citing papers authored by Iman Tavassoly

Since Specialization
Citations

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

Fields of papers citing papers by Iman Tavassoly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iman Tavassoly

This figure shows the co-authorship network connecting the top 25 collaborators of Iman Tavassoly. A scholar is included among the top collaborators of Iman Tavassoly 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 Iman Tavassoly. Iman Tavassoly 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.
Manca, Paolo, Chin‐Tung Chen, Christina Y. Lee, et al.. (2025). Ultrasensitive ctDNA monitoring for organ preservation in patients with locally advanced rectal cancer. npj Precision Oncology. 10(1). 8–8.
2.
Tran, Ivy, Kristyn Galbraith, Sharon L. Gardner, et al.. (2023). Ultrasensitive detection and monitoring of central nervous system tumors from plasma using personalized whole-genome ctDNA profiling.. Journal of Clinical Oncology. 41(16_suppl). 2064–2064. 2 indexed citations
3.
Nordentoft, Iver, Sia V. Lindskrog, Karin Birkenkamp‐Demtröder, et al.. (2023). Accuracy of genome-wide mutational analysis for tumor-informed ctDNA-guided MRD monitoring in bladder cancer.. Journal of Clinical Oncology. 41(16_suppl). 4589–4589. 1 indexed citations
4.
Yang, Xingbo, Matthias Heinemann, Jonathon Howard, et al.. (2021). Physical bioenergetics: Energy fluxes, budgets, and constraints in cells. Proceedings of the National Academy of Sciences. 118(26). 69 indexed citations
5.
Mehrpooya, Adel, et al.. (2021). High dimensionality reduction by matrix factorization for systems pharmacology. Briefings in Bioinformatics. 23(1). 26 indexed citations
6.
7.
Tavassoly, Omid & Iman Tavassoly. (2021). Pharmacological Functionalization of Protein-Based Nanorobots as a Novel Tool for Drug Delivery in Cancer. ACS Pharmacology & Translational Science. 4(4). 1463–1467. 1 indexed citations
8.
Tavassoly, Omid, Takashi Sato, & Iman Tavassoly. (2020). Inhibition of Brain Epidermal Growth Factor Receptor Activation: A Novel Target in Neurodegenerative Diseases and Brain Injuries. Molecular Pharmacology. 98(1). 13–22. 47 indexed citations
9.
Tavassoly, Omid, Farinaz Safavi, & Iman Tavassoly. (2020). Heparin-binding Peptides as Novel Therapies to Stop SARS-CoV-2 Cellular Entry and Infection. Molecular Pharmacology. 98(5). 612–619. 33 indexed citations
10.
Azadi, Amir, et al.. (2019). Dynamic modeling of signal transduction by mTOR complexes in cancer. Journal of Theoretical Biology. 483. 109992–109992. 10 indexed citations
11.
12.
Tavassoly, Iman, Yuan Hu, Shan Zhao, et al.. (2019). Genomic signatures defining responsiveness to allopurinol and combination therapy for lung cancer identified by systems therapeutics analyses. Molecular Oncology. 13(8). 1725–1743. 24 indexed citations
13.
Tavassoly, Iman, et al.. (2019). A Systems Biology Roadmap to Decode mTOR Control System in Cancer. Interdisciplinary Sciences Computational Life Sciences. 12(1). 1–11. 27 indexed citations
14.
Tavassoly, Iman, Joseph Goldfarb, & Ravi Iyengar. (2018). Systems biology primer: the basic methods and approaches. Essays in Biochemistry. 62(4). 487–500. 113 indexed citations
15.
Hu, Mufeng, Evren U. Azeloglu, Khanh‐Hoa Tran‐Ba, et al.. (2017). A biomimetic gelatin-based platform elicits a pro-differentiation effect on podocytes through mechanotransduction. Scientific Reports. 7(1). 43934–43934. 29 indexed citations
16.
Parmar, Jignesh H., Katherine L. Cook, Ayesha N. Shajahan‐Haq, et al.. (2013). Modelling the effect of GRP78 on anti-oestrogen sensitivity and resistance in breast cancer. Interface Focus. 3(4). 20130012–20130012. 22 indexed citations
17.
Tyson, John J., William T. Baumann, Chun Chen, et al.. (2011). Dynamic modelling of oestrogen signalling and cell fate in breast cancer cells. Nature reviews. Cancer. 11(7). 523–532. 147 indexed citations
18.
Clarke, Robert, Ayesha N. Shajahan‐Haq, Yue Wang, et al.. (2011). Endoplasmic reticulum stress, the unfolded protein response, and gene network modeling in antiestrogen resistant breast cancer. Hormone Molecular Biology and Clinical Investigation. 5(1). 35–44. 47 indexed citations
19.
Tavassoly, Iman, et al.. (2007). Chaos game representation of mitochondrial DNA: is it useful in phylogenetic studies?. BMC Systems Biology. 1(S1). 1 indexed citations
20.
Tavassoly, Iman, et al.. (2007). Three Dimensional Chaos Game Representation of Genomic Sequences. 219–223. 3 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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