Michael De Lay

1.1k total citations
10 papers, 900 citations indexed

About

Michael De Lay is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Michael De Lay has authored 10 papers receiving a total of 900 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Genetics and 4 papers in Immunology. Recurrent topics in Michael De Lay's work include Cancer, Hypoxia, and Metabolism (3 papers), Glioma Diagnosis and Treatment (3 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Michael De Lay is often cited by papers focused on Cancer, Hypoxia, and Metabolism (3 papers), Glioma Diagnosis and Treatment (3 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Michael De Lay collaborates with scholars based in United States and Japan. Michael De Lay's co-authors include Manish K. Aghi, Arman Jahangiri, Michal O. Nowicki, E. Antonio Chiocca, Sean Lawler, Jeff Palatini, Jakub Godlewski, James R. Van Brocklyn, Michael C. Ostrowski and Gerard J. Nuovo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and Molecular Cell.

In The Last Decade

Michael De Lay

10 papers receiving 885 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael De Lay United States	8	546	387	224	206	171	10	900
Shaoyan Xi China	20	540 1.0×	330 0.9×	137 0.6×	298 1.4×	129 0.8×	60	1.1k
John F. de Groot United States	11	384 0.7×	238 0.6×	417 1.9×	218 1.1×	175 1.0×	14	856
Anke Waha Germany	19	967 1.8×	213 0.6×	215 1.0×	166 0.8×	68 0.4×	29	1.2k
Catherine Richon France	18	608 1.1×	419 1.1×	233 1.0×	391 1.9×	243 1.4×	32	1.2k
Ingrid Moen Norway	8	393 0.7×	415 1.1×	263 1.2×	187 0.9×	76 0.4×	16	934
Ningyi Tiao United States	10	436 0.8×	156 0.4×	270 1.2×	218 1.1×	177 1.0×	13	768
Annique M. Duyverman United States	8	391 0.7×	348 0.9×	181 0.8×	593 2.9×	177 1.0×	8	1.1k
Francesca Orzan Italy	15	393 0.7×	280 0.7×	176 0.8×	381 1.8×	93 0.5×	24	905
Ulrike Ulbricht Germany	7	546 1.0×	297 0.8×	293 1.3×	162 0.8×	105 0.6×	8	854
Mark D. Hjelmeland United States	7	543 1.0×	144 0.4×	160 0.7×	246 1.2×	99 0.6×	8	782

Countries citing papers authored by Michael De Lay

Since Specialization

Citations

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

Fields of papers citing papers by Michael De Lay

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael De Lay. 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 Michael De Lay. The network helps show where Michael De Lay may publish in the future.

Co-authorship network of co-authors of Michael De Lay

This figure shows the co-authorship network connecting the top 25 collaborators of Michael De Lay. A scholar is included among the top collaborators of Michael De Lay 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 Michael De Lay. Michael De Lay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Castro, Brandyn, Patrick M. Flanigan, Arman Jahangiri, et al.. (2017). Macrophage migration inhibitory factor downregulation: a novel mechanism of resistance to anti-angiogenic therapy. Oncogene. 36(26). 3749–3759. 111 indexed citations

Kuang, Ruby, Arman Jahangiri, Alan Nguyen, et al.. (2017). GLUT3 upregulation promotes metabolic reprogramming associated with antiangiogenic therapy resistance. JCI Insight. 2(2). e88815–e88815. 52 indexed citations

Jahangiri, Arman, Alan Nguyen, Ankush Chandra, et al.. (2017). Cross-activating c-Met/β1 integrin complex drives metastasis and invasive resistance in cancer. Proceedings of the National Academy of Sciences. 114(41). E8685–E8694. 62 indexed citations

Sidorov, Maxim, Arman Jahangiri, Sungwon Han, et al.. (2016). 340 c-Met/β1 Integrin. Neurosurgery. 63(Supplement 1). 199–200. 4 indexed citations

Castro, Brandyn, Arman Jahangiri, Ruby Kuang, et al.. (2015). MTR-01BEVACIZUMAB-INDUCED MIF DEPLETION: A NOVEL RESISTANCE MECHANISM IN GLIOBLASTOMA. Neuro-Oncology. 17(suppl 5). v124.1–v124. 8 indexed citations

Jahangiri, Arman, Michael De Lay, Liane M. Miller, et al.. (2013). Gene Expression Profile Identifies Tyrosine Kinase c-Met as a Targetable Mediator of Antiangiogenic Therapy Resistance. Clinical Cancer Research. 19(7). 1773–1783. 161 indexed citations

Hu, Yulong, Arman Jahangiri, Michael De Lay, & Manish K. Aghi. (2012). Hypoxia-induced tumor cell autophagy mediates resistance to anti-angiogenic therapy. Autophagy. 8(6). 979–981. 54 indexed citations

Godlewski, Jakub, Michal O. Nowicki, Agnieszka Bronisz, et al.. (2010). MicroRNA-451 Regulates LKB1/AMPK Signaling and Allows Adaptation to Metabolic Stress in Glioma Cells. Molecular Cell. 37(5). 620–632. 350 indexed citations

Lucas, David, Ryan B. Edwards, Michael De Lay, et al.. (2007). The Plant-Derived Agent Silvestrol Has B-Cell Selective Activity In Vitro in Chronic Lymphocytic Leukemia Patient Cells and In Vivo in the Tcl-1 Mouse Model of CLL.. Blood. 110(11). 3123–3123. 1 indexed citations

10.

Johnson, Amy J., David Lucas, Natarajan Muthusamy, et al.. (2006). Characterization of the TCL-1 transgenic mouse as a preclinical drug development tool for human chronic lymphocytic leukemia. Blood. 108(4). 1334–1338. 97 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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