Mia Rushe

964 total citations
12 papers, 666 citations indexed

About

Mia Rushe is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mia Rushe has authored 12 papers receiving a total of 666 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 5 papers in Molecular Biology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mia Rushe's work include Immunotherapy and Immune Responses (5 papers), T-cell and B-cell Immunology (5 papers) and Immune Cell Function and Interaction (4 papers). Mia Rushe is often cited by papers focused on Immunotherapy and Immune Responses (5 papers), T-cell and B-cell Immunology (5 papers) and Immune Cell Function and Interaction (4 papers). Mia Rushe collaborates with scholars based in United States, Czechia and South Korea. Mia Rushe's co-authors include Lawrence J. Stern, Aleksey Lomakin, Aaron K. Sato, George B. Benedek, Alexey A. Lugovskoy, P. Ann Boriack‐Sjodin, Laura Silvian, Matthew Jarpe, Herman van Vlijmen and Elizabeth Mellins and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Biochemistry.

In The Last Decade

Mia Rushe

12 papers receiving 654 citations

Peers

Mia Rushe
Mihai L. Azoitei United States
Lee W. Thompson United States
Ben G. Wen United States
Fritz Rudert Germany
A. Neil Barclay United Kingdom
Jean K. Stewart United States
Andrew Riddell United Kingdom
Mia Rushe
Citations per year, relative to Mia Rushe Mia Rushe (= 1×) peers Yuki Fujii

Countries citing papers authored by Mia Rushe

Since Specialization
Citations

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

Fields of papers citing papers by Mia Rushe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mia Rushe

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

All Works

12 of 12 papers shown
1.
Arndt, Joseph W., Yuting Liu, Mia Rushe, et al.. (2020). Functional activity of anti-LINGO-1 antibody opicinumab requires target engagement at a secondary binding site. mAbs. 12(1). 1713648–1713648. 18 indexed citations
2.
Sopko, Richelle, Joshua W. Mugford, Andreas Lehmann, et al.. (2017). Engineering potent long-acting variants of the Wnt inhibitor DKK2. Protein Engineering Design and Selection. 30(5). 359–372. 3 indexed citations
3.
Marcotte, D.J., Mia Rushe, Robert M. Arduini, et al.. (2016). Germinal‐center kinase‐like kinase co‐crystal structure reveals a swapped activation loop and C‐terminal extension. Protein Science. 26(2). 152–162. 16 indexed citations
4.
Rushe, Mia, Laura Silvian, Sarah A. Bixler, et al.. (2008). Structure of a NEMO/IKK-Associating Domain Reveals Architecture of the Interaction Site. Structure. 16(5). 798–808. 109 indexed citations
5.
Silvian, Laura, Ping Jin, Paul Carmillo, et al.. (2006). Artemin Crystal Structure Reveals Insights into Heparan Sulfate Binding. Biochemistry. 45(22). 6801–6812. 40 indexed citations
6.
Reid, Carl E., Mia Rushe, Matthew Jarpe, et al.. (2006). Structure activity relationships of monocyte chemoattractant proteins in complex with a blocking antibody. Protein Engineering Design and Selection. 19(7). 317–324. 29 indexed citations
7.
Clark, Louis A., P. Ann Boriack‐Sjodin, John Eldredge, et al.. (2006). Affinity enhancement of an in vivo matured therapeutic antibody using structure‐based computational design. Protein Science. 15(5). 949–960. 136 indexed citations
8.
Carven, Gregory J., Sriram Chitta, I Hilgert, et al.. (2004). Monoclonal Antibodies Specific for the Empty Conformation of HLA-DR1 Reveal Aspects of the Conformational Change Associated with Peptide Binding. Journal of Biological Chemistry. 279(16). 16561–16570. 43 indexed citations
9.
Ge, Qing, Jennifer D. Stone, Michael T. Thompson, et al.. (2002). Soluble peptide–MHC monomers cause activation of CD8 + T cells through transfer of the peptide to T cell MHC molecules. Proceedings of the National Academy of Sciences. 99(21). 13729–13734. 66 indexed citations
10.
Busch, Robert, et al.. (2001). The kinetic basis of peptide exchange catalysis by HLA-DM. Proceedings of the National Academy of Sciences. 98(22). 12450–12455. 61 indexed citations
11.
Sato, Aaron K., Mia Rushe, Aleksey Lomakin, et al.. (2000). Determinants of the Peptide-induced Conformational Change in the Human Class II Major Histocompatibility Complex Protein HLA-DR1. Journal of Biological Chemistry. 275(3). 2165–2173. 72 indexed citations
12.
Sato, Aaron K., et al.. (1999). A Conformational Change in the Human Major Histocompatibility Complex Protein HLA-DR1 Induced by Peptide Binding. Biochemistry. 38(18). 5878–5887. 73 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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