Michael Churchill

2.3k total citations
21 papers, 783 citations indexed

About

Michael Churchill is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Michael Churchill has authored 21 papers receiving a total of 783 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Oncology and 4 papers in Hematology. Recurrent topics in Michael Churchill's work include Acute Myeloid Leukemia Research (2 papers), Epigenetics and DNA Methylation (2 papers) and Immune Cell Function and Interaction (2 papers). Michael Churchill is often cited by papers focused on Acute Myeloid Leukemia Research (2 papers), Epigenetics and DNA Methylation (2 papers) and Immune Cell Function and Interaction (2 papers). Michael Churchill collaborates with scholars based in United States, Japan and Hong Kong. Michael Churchill's co-authors include Philip E. Dawson, Stephen B. H. Kent, M. Reza Ghadiri, Duncan E. McRee, Melissa M. Fitzgerald, David B. Goodin, Siddhartha Mukherjee, Daniel A. Kraut, Daniel Herschlag and Timothy C. Wang and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and Journal of Clinical Oncology.

In The Last Decade

Michael Churchill

20 papers receiving 763 citations

Peers

Michael Churchill

ONCOL

IMMUN

NHEP

Houbi Nguyen United States

Wladimir Labeikovsky United States

Jean‐Manuel Segura Switzerland

James M. Gruschus United States

Peter F. Flynn United States

Keith L. Constantine United States

Michael S. Marlow United States

Eva de Alba United States

Masakazu Fukuda Japan

Taras V. Pogorelov United States

Houbi Nguyen United States

Michael Churchill

1.0k ×2.2

80 ×0.5

81 ×0.7

ONCOL

41 ×0.6

IMMUN

29 ×0.4

NHEP

Citations per year, relative to Michael Churchill Michael Churchill (= 1×) peers Houbi Nguyen

Countries citing papers authored by Michael Churchill

Since Specialization

Citations

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

Fields of papers citing papers by Michael Churchill

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Churchill

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

All Works

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20 of 20 papers shown

Kon, Ning, Michael Churchill, Huan Li, et al.. (2020). Robust p53 Stabilization Is Dispensable for Its Activation and Tumor Suppressor Function. Cancer Research. 81(4). 935–944. 18 indexed citations

Churchill, Michael, Franz X. Schaub, Rachele Rosati, et al.. (2020). Predictive value of a CLIA-approved organoid based drug sensitivity test.. Journal of Clinical Oncology. 38(15_suppl). 3630–3630. 4 indexed citations

Schaub, Franz X., Michael Churchill, Rachele Rosati, et al.. (2020). Abstract 818: Organoid based functional test to predict personalized treatment in cholangiocarcinoma. Cancer Research. 80(16_Supplement). 818–818. 2 indexed citations

Rosati, Rachele, Michael Churchill, Reid Shaw, et al.. (2018). Abstract 1619: Personalized medicine: A CLIA-certified high-throughput drug screening platform for ovarian cancer. Cancer Research. 78(13_Supplement). 1619–1619. 3 indexed citations

Chen, Xiaowei, Yoshihiro Takemoto, Huan Deng, et al.. (2017). Histidine decarboxylase (HDC)-expressing granulocytic myeloid cells induce and recruit Foxp3⁺ regulatory T cells in murine colon cancer. OncoImmunology. 6(3). e1290034–e1290034. 38 indexed citations

Chen, Xiaowei, Michael Churchill, Karan Nagar, et al.. (2015). IL-17 producing mast cells promote the expansion of myeloid-derived suppressor cells in a mouse allergy model of colorectal cancer. Oncotarget. 6(32). 32966–32979. 28 indexed citations

Weisberg, Stuart P., Matthew Smith-Raska, Ji Zhang, et al.. (2014). ZFX Controls Propagation and Prevents Differentiation of Acute T-Lymphoblastic and Myeloid Leukemia. Cell Reports. 6(3). 528–540. 22 indexed citations

Diallo, A., J. W. Hughes, M. Greenwald, et al.. (2014). Observation of Edge Instability Limiting the Pedestal Growth in Tokamak Plasmas. Physical Review Letters. 112(11). 115001–115001. 67 indexed citations

Avagyan, Serine, Michael Churchill, Kenta Yamamoto, et al.. (2014). Hematopoietic stem cell dysfunction underlies the progressive lymphocytopenia in XLF/Cernunnos deficiency. Blood. 124(10). 1622–1625. 15 indexed citations

10.

Worthley, Daniel L., Yiling Si, Michael Quante, et al.. (2013). Bone marrow cells as precursors of the tumor stroma. Experimental Cell Research. 319(11). 1650–1656. 20 indexed citations

11.

Ewalt, Mark D., Naomi Galili, Muhammad Ali Mumtaz, et al.. (2011). DNMT3a mutations in high-risk myelodysplastic syndrome parallel those found in acute myeloid leukemia. Blood Cancer Journal. 1(3). e9–e9. 26 indexed citations

12.

Kraut, Daniel A., et al.. (2009). Evaluating the Potential for Halogen Bonding in the Oxyanion Hole of Ketosteroid Isomerase Using Unnatural Amino Acid Mutagenesis. ACS Chemical Biology. 4(4). 269–273. 56 indexed citations

13.

Niemann, Stephan, Hiroaki Kanki, Yasuyuki Fukui, et al.. (2007). Genetic ablation of NMDA receptor subunit NR3B in mouse reveals motoneuronal and nonmotoneuronal phenotypes. European Journal of Neuroscience. 26(6). 1407–1420. 39 indexed citations

14.

Churchill, Michael, et al.. (2007). Hardware-accelerated cone-beam reconstruction on a mobile C-arm. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6510. 65105S–65105S. 14 indexed citations

15.

Niemann, Stephan, John E. Landers, Michael Churchill, et al.. (2007). Motoneuron-specificNR3Bgene. Neurology. 70(9). 666–676. 19 indexed citations

16.

Neuman, Benjamin W., David A. Stein, Andrew Kroeker, et al.. (2005). Inhibition, Escape, and Attenuated Growth of Severe Acute Respiratory Syndrome Coronavirus Treated with Antisense Morpholino Oligomers. Journal of Virology. 79(15). 9665–9676. 86 indexed citations

17.

Kamikubo, Yuichi, Gerard Kroon, Scott A. Curriden, et al.. (2004). Disulfide Bonding Arrangements in Active Forms of the Somatomedin B Domain of Human Vitronectin. Biochemistry. 43(21). 6519–6534. 33 indexed citations

18.

Dawson, Philip E., Michael Churchill, M. Reza Ghadiri, & Stephen B. H. Kent. (1997). Modulation of Reactivity in Native Chemical Ligation through the Use of Thiol Additives. Journal of the American Chemical Society. 119(19). 4325–4329. 218 indexed citations

19.

Fitzgerald, Melissa M., Michael Churchill, Duncan E. McRee, & David B. Goodin. (1994). Small Molecule Binding to an Artificially Created Cavity at the Active Site of Cytochrome c Peroxidase. Biochemistry. 33(13). 3807–3818. 74 indexed citations

20.

Churchill, Michael. (1968). Vector Plotting Display. Review of Scientific Instruments. 39(3). 351–352.

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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