Joel Johansson

15.7k total citations · 2 hit papers
93 papers, 6.0k citations indexed

About

Joel Johansson is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Joel Johansson has authored 93 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Molecular Biology, 36 papers in Hematology and 31 papers in Oncology. Recurrent topics in Joel Johansson's work include Cell death mechanisms and regulation (23 papers), Chronic Lymphocytic Leukemia Research (21 papers) and Multiple Myeloma Research and Treatments (19 papers). Joel Johansson is often cited by papers focused on Cell death mechanisms and regulation (23 papers), Chronic Lymphocytic Leukemia Research (21 papers) and Multiple Myeloma Research and Treatments (19 papers). Joel Johansson collaborates with scholars based in United States, France and Australia. Joel Johansson's co-authors include Tony Hunter, Han-kuei Huang, Andrew J. Souers, Claudio A.P. Joazeiro, Wayne J. Fairbrother, Avi Ashkenazi, Simon S. Wing, Yun‐Cai Liu, Scott A. Ness and Huaiyu Sun and has published in prestigious journals such as Science, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Joel Johansson

91 papers receiving 5.9k citations

Hit Papers

The Tyrosine Kinase Negative Regulator c-Cbl as a RING-Ty... 1999 2026 2008 2017 1999 2017 250 500 750

Peers

Joel Johansson
Mohamed Rahmani United States
Warren Fiskus United States
David J. Bearss United States
Peter Atadja United States
Keith Dredge United States
Grazia Ambrosini United States
Lori Hazlehurst United States
Tomasz Skórski United States
Mohamed Rahmani United States
Joel Johansson
Citations per year, relative to Joel Johansson Joel Johansson (= 1×) peers Mohamed Rahmani

Countries citing papers authored by Joel Johansson

Since Specialization
Citations

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

Fields of papers citing papers by Joel Johansson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joel Johansson

This figure shows the co-authorship network connecting the top 25 collaborators of Joel Johansson. A scholar is included among the top collaborators of Joel Johansson 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 Joel Johansson. Joel Johansson 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.
Buono, Roberta, Shannon M. Matulis, Vikas A. Gupta, et al.. (2023). Statin-induced Mitochondrial Priming Sensitizes Multiple Myeloma Cells to BCL2 and MCL-1 Inhibitors. Cancer Research Communications. 3(12). 2497–2509. 3 indexed citations
2.
Jin, Sha, Dan Cojocari, Julie J. Purkal, et al.. (2020). 5-Azacitidine Induces NOXA to Prime AML Cells for Venetoclax-Mediated Apoptosis. Clinical Cancer Research. 26(13). 3371–3383. 126 indexed citations
3.
Zervantonakis, Ioannis K., Laura M. Selfors, Sangeetha Palakurthi, et al.. (2019). Combined MEK and BCL-2/XL Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient–Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness. Molecular Cancer Therapeutics. 18(3). 642–655. 36 indexed citations
4.
Zoeller, Jason J., Krishan Taneja, Benjamin Y. Tan, et al.. (2019). Neutralization of BCL-2/XL Enhances the Cytotoxicity of T-DM1 In Vivo. Molecular Cancer Therapeutics. 18(6). 1115–1126. 25 indexed citations
5.
Heisey, Daniel A.R., Timothy L. Lochmann, Konstantinos V. Floros, et al.. (2018). The Ewing Family of Tumors Relies on BCL-2 and BCL-XL to Escape PARP Inhibitor Toxicity. Clinical Cancer Research. 25(5). 1664–1675. 22 indexed citations
6.
Rahmani, Mohamed, Xin‐Yan Pei, Rebecca E. Parker, et al.. (2018). Cotargeting BCL-2 and PI3K Induces BAX-Dependent Mitochondrial Apoptosis in AML Cells. Cancer Research. 78(11). 3075–3086. 112 indexed citations
7.
Cathelin, Séverine, David Sharon, Dan Cojocari, et al.. (2018). Combination of Enasidenib and Venetoclax Shows Superior Anti-Leukemic Activity Against IDH2 Mutated AML in Patient-Derived Xenograft Models. Blood. 132(Supplement 1). 562–562. 23 indexed citations
8.
Lochmann, Timothy L., Konstantinos V. Floros, Mitra Naseri, et al.. (2017). Venetoclax Is Effective in Small-Cell Lung Cancers with High BCL-2 Expression. Clinical Cancer Research. 24(2). 360–369. 93 indexed citations
9.
Mali, Raghuveer Singh, Elisabeth A. Lasater, Kelly Doyle, et al.. (2017). FLT3-ITD Activation Mediates Resistance to the BCL-2 Selective Antagonist, Venetoclax, in FLT3-ITD Mutant AML Models. Blood. 130. 1348–1348. 17 indexed citations
10.
Roberts, Andrew W., Tu Xu, Jia Jia, et al.. (2017). Do Statins Enhance the Anti-Cancer Activity of Venetoclax?. Blood. 130. 1737–1737. 1 indexed citations
12.
Punnoose, Elizabeth A., Joel Johansson, Franklin Peale, et al.. (2016). Expression Profile of BCL-2, BCL-XL, and MCL-1 Predicts Pharmacological Response to the BCL-2 Selective Antagonist Venetoclax in Multiple Myeloma Models. Molecular Cancer Therapeutics. 15(5). 1132–1144. 223 indexed citations
13.
Zhāng, Qí, Lina Han, Ce Shi, et al.. (2016). Upregulation of MAPK/MCL-1 Maintaining Mitochondrial Oxidative Phosphorylation Confers Acquired Resistance to BCL-2 Inhibitor Venetoclax in AML. Blood. 128(22). 101–101. 5 indexed citations
14.
Xiao, Yu, Paul Nimmer, George S. Sheppard, et al.. (2015). MCL-1 Is a Key Determinant of Breast Cancer Cell Survival: Validation of MCL-1 Dependency Utilizing a Highly Selective Small Molecule Inhibitor. Molecular Cancer Therapeutics. 14(8). 1837–1847. 89 indexed citations
15.
Chen, Jun, Sha Jin, Xiaoli Huang, et al.. (2011). The Bcl-2/Bcl-XL/Bcl-w Inhibitor, Navitoclax, Enhances the Activity of Chemotherapeutic Agents In Vitro and In Vivo. Molecular Cancer Therapeutics. 10(12). 2340–2349. 119 indexed citations
16.
Liu, Xuesong, Edward K. Han, Mark G. Anderson, et al.. (2009). Acquired Resistance to Combination Treatment with Temozolomide and ABT-888 Is Mediated by Both Base Excision Repair and Homologous Recombination DNA Repair Pathways. Molecular Cancer Research. 7(10). 1686–1692. 77 indexed citations
17.
Sun, Huaiyu, Joel Johansson, & Tony Hunter. (2007). Conserved function of RNF4 family proteins in eukaryotes: targeting a ubiquitin ligase to SUMOylated proteins. The EMBO Journal. 26(18). 4102–4112. 248 indexed citations
18.
19.
Zhu, Changjun, Jian Zhao, Marina Bibikova, et al.. (2005). Functional Analysis of Human Microtubule-based Motor Proteins, the Kinesins and Dyneins, in Mitosis/Cytokinesis Using RNA Interference. Molecular Biology of the Cell. 16(7). 3187–3199. 335 indexed citations
20.
Johansson, Joel, Päivi J. Koskinen, Eeva-Marja Rainio, et al.. (1998). Pim-1 Kinase and p100 Cooperate to Enhance c-Myb Activity. Molecular Cell. 2(4). 417–425. 228 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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