Mikhail Akimov

3.7k total citations
78 papers, 1.5k citations indexed

About

Mikhail Akimov is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Mikhail Akimov has authored 78 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 22 papers in Pulmonary and Respiratory Medicine and 19 papers in Oncology. Recurrent topics in Mikhail Akimov's work include Lung Cancer Treatments and Mutations (20 papers), Heat shock proteins research (12 papers) and Cannabis and Cannabinoid Research (9 papers). Mikhail Akimov is often cited by papers focused on Lung Cancer Treatments and Mutations (20 papers), Heat shock proteins research (12 papers) and Cannabis and Cannabinoid Research (9 papers). Mikhail Akimov collaborates with scholars based in Russia, Switzerland and United States. Mikhail Akimov's co-authors include Enriqueta Felip, В. В. Безуглов, N. M. Gretskaya, Wu‐Chou Su, Sylvia Zhao, Yi‐Long Wu, Bin Peng, Dae Ho Lee, James Chih‐Hsin Yang and Myung‐Ju Ahn and has published in prestigious journals such as Journal of Clinical Oncology, Cancer and Cancer Research.

In The Last Decade

Mikhail Akimov

74 papers receiving 1.4k citations

Peers

Mikhail Akimov
Paula Kaplan‐Lefko United States
Amanda J. Craig United States
Barbara Mroczkowski United States
Sven A. Lang Germany
Sébastien Jeay Switzerland
John E. Monahan United States
Elaine S. E. Stokes United Kingdom
Carolyn Cao United States
Paula Kaplan‐Lefko United States
Mikhail Akimov
Citations per year, relative to Mikhail Akimov Mikhail Akimov (= 1×) peers Paula Kaplan‐Lefko

Countries citing papers authored by Mikhail Akimov

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Akimov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikhail Akimov

This figure shows the co-authorship network connecting the top 25 collaborators of Mikhail Akimov. A scholar is included among the top collaborators of Mikhail Akimov 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 Mikhail Akimov. Mikhail Akimov 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.
Akimov, Mikhail, et al.. (2024). The Interaction of the Endocannabinoid Anandamide and Paracannabinoid Lysophosphatidylinositol during Cell Death Induction in Human Breast Cancer Cells. International Journal of Molecular Sciences. 25(4). 2271–2271. 2 indexed citations
2.
Akimov, Mikhail, et al.. (2023). The Mechanisms of GPR55 Receptor Functional Selectivity during Apoptosis and Proliferation Regulation in Cancer Cells. International Journal of Molecular Sciences. 24(6). 5524–5524. 9 indexed citations
3.
Akimov, Mikhail, et al.. (2023). Multicomponent Lipid Nanoparticles for RNA Transfection. Pharmaceutics. 15(4). 1289–1289. 8 indexed citations
4.
Heist, Rebecca S., Johan Vansteenkiste, Egbert F. Smit, et al.. (2021). MO01.21 Phase 2 GEOMETRY Mono-1 Study: Capmatinib in Patients with METex14-mutated Advanced Non-Small Cell Lung Cancer who Received Prior Immunotherapy. Journal of Thoracic Oncology. 16(1). S24–S25.
5.
Akimov, Mikhail, et al.. (2020). The Influence of the Cholesterol Level in Cells on Endovanilloid Cytotoxicity. Doklady Biochemistry and Biophysics. 493(1). 167–170. 1 indexed citations
6.
Schüler, Martin, Rossana Berardi, Wan‐Teck Lim, et al.. (2020). Molecular correlates of response to capmatinib in advanced non-small-cell lung cancer: clinical and biomarker results from a phase I trial. Annals of Oncology. 31(6). 789–797. 72 indexed citations
7.
Gretskaya, N. M., Roman Akasov, S. V. Burov, et al.. (2020). Novel bexarotene derivatives: Synthesis and cytotoxicity evaluation for glioma cells in 2D and 3D in vitro models. European Journal of Pharmacology. 883. 173346–173346. 10 indexed citations
8.
Akimov, Mikhail, et al.. (2019). Neuroprotective Action of Amidic Neurolipins in Models of Neurotoxicity on the Culture of Human Neural-Like Cells SH-SY5Y. Doklady Biochemistry and Biophysics. 485(1). 141–144. 3 indexed citations
9.
Tan, Daniel Shao-Weng, Dae Ho Lee, Ross A. Soo, et al.. (2017). P3.02b-117 Phase Ib Results from a Study of Capmatinib (INC280) + EGF816 in Patients with EGFR-Mutant Non-Small Cell Lung Cancer (NSCLC). Journal of Thoracic Oncology. 12(1). S1264–S1265. 6 indexed citations
10.
Akimov, Mikhail, et al.. (2017). N-acyl dopamines induce apoptosis in PC12 cell line via the GPR55 receptor activation. Doklady Biochemistry and Biophysics. 474(1). 155–158. 10 indexed citations
11.
Akimov, Mikhail, et al.. (2016). N-acyl dopamines induce cell death in PC12 cell line via induction of nitric oxide generation and oxidative stress. Doklady Biochemistry and Biophysics. 467(1). 81–84. 6 indexed citations
12.
Rybkin, Igor I., Egbert F. Smit, Hans‐Georg Kopp, et al.. (2016). PS01.60: Ph Ib/II, Trial of INC280 ± Erlotinib vs Platinum + Pemetrexed in Adult pts with EGFR-Mutated, cMET amplified, EGFR TKI Resistant, Advanced NSCLC. Journal of Thoracic Oncology. 11(11). S307–S308. 1 indexed citations
13.
Bauer, Todd M., Martin Schüler, Rossana Berardi, et al.. (2016). MINI01.03: Phase (Ph) I Study of the Safety and Efficacy of the cMET Inhibitor Capmatinib (INC280) in Patients with Advanced cMET+ NSCLC. Journal of Thoracic Oncology. 11(11). S257–S258. 11 indexed citations
14.
Roman, Danielle, James N. Ver Hoeve, Heiko S. Schadt, et al.. (2016). Ocular toxicity of AUY922 in pigmented and albino rats. Toxicology and Applied Pharmacology. 309. 55–62. 5 indexed citations
15.
Gaykema, Sietske B.M., Carolien P. Schröder, Joanna Vitfell-Rasmussen, et al.. (2014). 89Zr-trastuzumab and 89Zr-bevacizumab PET to Evaluate the Effect of the HSP90 Inhibitor NVP-AUY922 in Metastatic Breast Cancer Patients. Clinical Cancer Research. 20(15). 3945–3954. 95 indexed citations
16.
Akimov, Mikhail, et al.. (2014). Some aspects of the mechanism of cell death induction by the lipids of N-acyl dopamine family in the PC12 cancer cell line. Anticancer Research. 34(10). 5797–5800. 4 indexed citations
17.
Sessa, Cristiana, Geoffrey I. Shapiro, Kapil N. Bhalla, et al.. (2013). First-in-Human Phase I Dose-Escalation Study of the HSP90 Inhibitor AUY922 in Patients with Advanced Solid Tumors. Clinical Cancer Research. 19(13). 3671–3680. 119 indexed citations
18.
Wainberg, Zev A., Adrian Anghel, Amrita Desai, et al.. (2013). Inhibition of HSP90 with AUY922 Induces Synergy in HER2-Amplified Trastuzumab-Resistant Breast and Gastric Cancer. Molecular Cancer Therapeutics. 12(4). 509–519. 58 indexed citations
19.
Akimov, Mikhail, et al.. (2009). Sulfation of N-acyl dopamines in rat tissues. Biochemistry (Moscow). 74(6). 681–685. 9 indexed citations
20.
Ranson, Malcolm, Martin Reck, Alan Anthoney, et al.. (2007). 6587 POSTER A phase IB, dose-finding study of erlotinib in combination with pemetrexed in patients with advanced (stage IIIB/IV) non-small-cell lung cancer (NSCLC): a preliminary analysis of the BP18193 study. European Journal of Cancer Supplements. 5(4). 384–384. 2 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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