Richard Possemato

10.0k total citations · 3 hit papers
40 papers, 5.5k citations indexed

About

Richard Possemato is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Richard Possemato has authored 40 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 15 papers in Cancer Research and 6 papers in Physiology. Recurrent topics in Richard Possemato's work include Cancer, Hypoxia, and Metabolism (13 papers), Epigenetics and DNA Methylation (10 papers) and RNA modifications and cancer (7 papers). Richard Possemato is often cited by papers focused on Cancer, Hypoxia, and Metabolism (13 papers), Epigenetics and DNA Methylation (10 papers) and RNA modifications and cancer (7 papers). Richard Possemato collaborates with scholars based in United States, Japan and Netherlands. Richard Possemato's co-authors include Kıvanç Birsoy, David M. Sabatini, Vladislav O. Sviderskiy, Thales Papagiannakopoulos, Samantha Alvarez, William C. Hahn, Erdem M. Terzi, Walter W. Chen, Sylvia Adams and André L. Moreira and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Richard Possemato

34 papers receiving 5.5k citations

Hit Papers

NFS1 undergoes positive select... 2001 2026 2009 2017 2017 2001 2014 100 200 300 400 500

Peers

Richard Possemato
Xiang Ao China
Guangchao Sui United States
Da Fu China
Jie Zhou China
Jianjun Shen United States
Benjamin D. Hopkins United States
Sunmin Lee United States
Gong Yang China
Soichiro Yamamura United States
Richard Possemato
Citations per year, relative to Richard Possemato Richard Possemato (= 1×) peers Thales Papagiannakopoulos

Countries citing papers authored by Richard Possemato

Since Specialization
Citations

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

Fields of papers citing papers by Richard Possemato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Possemato

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Possemato. A scholar is included among the top collaborators of Richard Possemato 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 Richard Possemato. Richard Possemato 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
2.
Khan, Artem, Gökhan Ünlü, Rebecca C. Timson, et al.. (2025). Mitochondrial Glutathione Import Enables Breast Cancer Metastasis via Integrated Stress Response Signaling. Cancer Discovery. 15(12). 2437–2449.
3.
Sviderskiy, Vladislav O., Varshini Vasudevaraja, Luiz Gustavo Dubois, et al.. (2025). Metabolic profiling of adult and pediatric gliomas reveals enriched glucose availability in pediatric gliomas and increased fatty acid oxidation in adult gliomas. Acta Neuropathologica Communications. 13(1). 61–61.
4.
Schraink, Tobias, Lili M. Blumenberg, Tania J González-Robles, et al.. (2023). PhosphoDisco: A Toolkit for Co-regulated Phosphorylation Module Discovery in Phosphoproteomic Data. Molecular & Cellular Proteomics. 22(8). 100596–100596.
5.
Yang, Katharine, Ellie Ivanova, Jong Shin, et al.. (2023). Mitigation of Osteoclast‐Mediated Arthritic Bone Remodeling By Short Chain Fatty Acids. Arthritis & Rheumatology. 76(4). 647–659. 27 indexed citations
6.
McIntyre, Rebecca L., Marte Molenaars, Bauke V. Schomakers, et al.. (2022). Anti-retroviral treatment with zidovudine alters pyrimidine metabolism, reduces translation, and extends healthy longevity via ATF-4. Cell Reports. 42(1). 111928–111928. 12 indexed citations
7.
Sviderskiy, Vladislav O., Lili M. Blumenberg, Triantafyllia Karakousi, et al.. (2020). Hyperactive CDK2 Activity in Basal-like Breast Cancer Imposes a Genome Integrity Liability that Can Be Exploited by Targeting DNA Polymerase ε. Molecular Cell. 80(4). 682–698.e7. 31 indexed citations
8.
Wu, Lin, Kate E.R. Hollinshead, Yuhan Hao, et al.. (2020). Niche-Selective Inhibition of Pathogenic Th17 Cells by Targeting Metabolic Redundancy. Cell. 182(3). 641–654.e20. 83 indexed citations
9.
Amendola, Caroline R., Seth J. Parker, Ian M. Ahearn, et al.. (2019). KRAS4A directly regulates hexokinase 1. Nature. 576(7787). 482–486. 150 indexed citations
10.
Minton, Denise R., Minwoo Nam, Daniel J. McLaughlin, et al.. (2018). Serine Catabolism by SHMT2 Is Required for Proper Mitochondrial Translation Initiation and Maintenance of Formylmethionyl-tRNAs. Molecular Cell. 69(4). 610–621.e5. 146 indexed citations
11.
Alvarez, Samantha, Vladislav O. Sviderskiy, Erdem M. Terzi, et al.. (2017). NFS1 undergoes positive selection in lung tumours and protects cells from ferroptosis. DSpace@MIT (Massachusetts Institute of Technology). 150 indexed citations
12.
Alvarez, Samantha, Vladislav O. Sviderskiy, Erdem M. Terzi, et al.. (2017). NFS1 undergoes positive selection in lung tumours and protects cells from ferroptosis. Nature. 551(7682). 639–643. 587 indexed citations breakdown →
13.
Sayin, Volkan I., Sarah E. LeBoeuf, Simranjit X. Singh, et al.. (2017). Activation of the NRF2 antioxidant program generates an imbalance in central carbon metabolism in cancer. eLife. 6. 175 indexed citations
14.
Tsun, Zhi-Yang & Richard Possemato. (2015). Amino acid management in cancer. Seminars in Cell and Developmental Biology. 43. 22–32. 86 indexed citations
15.
Strohecker, Anne M., et al.. (2015). Identification of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase as a novel autophagy regulator by high content shRNA screening. Oncogene. 34(45). 5662–5676. 42 indexed citations
16.
Grabiner, Brian C., Valentina Nardi, Kıvanç Birsoy, et al.. (2014). A Diverse Array of Cancer-Associated MTOR Mutations Are Hyperactivating and Can Predict Rapamycin Sensitivity. Cancer Discovery. 4(5). 554–563. 318 indexed citations
17.
Sabatini, David M., Brian C. Grabiner, Valentina Nardi, et al.. (2014). A Diverse Array of Cancer-Associated MTOR Mutations Are Hyperactivating and Can Predict Rapamycin Sensitivity. PMC. 17 indexed citations
18.
Birsoy, Kıvanç, Richard Possemato, Franziska K. Lorbeer, et al.. (2014). Metabolic determinants of cancer cell sensitivity to glucose limitation and biguanides. Nature. 508(7494). 108–112. 558 indexed citations breakdown →
19.
Birsoy, Kıvanç, David M. Sabatini, & Richard Possemato. (2012). Untuning the tumor metabolic machine: Targeting cancer metabolism: a bedside lesson. Nature Medicine. 18(7). 1022–1023. 57 indexed citations
20.
Lugo‐Villarino, Geanncarlo, et al.. (2003). T-bet is required for optimal production of IFN-γ and antigen-specific T cell activation by dendritic cells. Proceedings of the National Academy of Sciences. 100(13). 7749–7754. 217 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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