Brian Tunquist

1.3k total citations
29 papers, 998 citations indexed

About

Brian Tunquist is a scholar working on Molecular Biology, Cell Biology and Hematology. According to data from OpenAlex, Brian Tunquist has authored 29 papers receiving a total of 998 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 15 papers in Cell Biology and 12 papers in Hematology. Recurrent topics in Brian Tunquist's work include Microtubule and mitosis dynamics (15 papers), Multiple Myeloma Research and Treatments (11 papers) and Ubiquitin and proteasome pathways (8 papers). Brian Tunquist is often cited by papers focused on Microtubule and mitosis dynamics (15 papers), Multiple Myeloma Research and Treatments (11 papers) and Ubiquitin and proteasome pathways (8 papers). Brian Tunquist collaborates with scholars based in United States, Spain and Palestinian Territory. Brian Tunquist's co-authors include James L. Maller, Markus S. Schwab, Duncan Walker, John D. Scott, Lorene K. Langeberg, Richard Woessner, Andrea L. Lewellyn, Frédéric Taïeb, Stefan Groß and B.Tibor Roberts and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Genes & Development.

In The Last Decade

Brian Tunquist

29 papers receiving 989 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian Tunquist United States 17 781 457 243 142 115 29 998
Fernando Ribeiro-Neto United States 15 825 1.1× 131 0.3× 72 0.3× 94 0.7× 20 0.2× 18 1.0k
Mary Risinger United States 16 594 0.8× 121 0.3× 24 0.1× 125 0.9× 127 1.1× 30 974
Barbara Cox United States 11 1.5k 1.9× 135 0.3× 65 0.3× 233 1.6× 64 0.6× 11 1.7k
Lucine Bosnoyan-Collins Canada 8 1.1k 1.4× 113 0.2× 90 0.4× 108 0.8× 63 0.5× 8 1.3k
Pamela M. Carroll United States 13 555 0.7× 110 0.2× 47 0.2× 82 0.6× 75 0.7× 22 765
Toshiyasu Goto Japan 15 772 1.0× 308 0.7× 102 0.4× 101 0.7× 9 0.1× 29 1.0k
Federico Diez Argentina 11 434 0.6× 336 0.7× 35 0.1× 114 0.8× 10 0.1× 11 875
Simon Descamps France 13 799 1.0× 509 1.1× 21 0.1× 352 2.5× 25 0.2× 20 1.2k
Dan Lin Canada 6 865 1.1× 579 1.3× 30 0.1× 101 0.7× 13 0.1× 13 1.2k
Gilles Chatelain France 20 760 1.0× 174 0.4× 45 0.2× 275 1.9× 11 0.1× 34 1.1k

Countries citing papers authored by Brian Tunquist

Since Specialization
Citations

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

Fields of papers citing papers by Brian Tunquist

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Tunquist

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Tunquist. A scholar is included among the top collaborators of Brian Tunquist 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 Brian Tunquist. Brian Tunquist 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.
Yaeger, Rona, Jean-François Martini, Lincoln W. Pasquina, et al.. (2025). Clinical Validity of FoundationOne Liquid CDx for Detection of BRAF V600E in Colorectal Cancer. Cancer Research Communications. 5(9). 1566–1573. 1 indexed citations
2.
Kaufman, Jonathan L., Myo Htut, Manish Agrawal, et al.. (2021). Filanesib plus bortezomib and dexamethasone in relapsed/refractory t(11;14) and 1q21 gain multiple myeloma. Cancer Medicine. 11(2). 358–370. 11 indexed citations
3.
Hernández-García, Susana, Laura San‐Segundo, Luís A. Corchete, et al.. (2017). The kinesin spindle protein inhibitor filanesib enhances the activity of pomalidomide and dexamethasone in multiple myeloma. Haematologica. 102(12). 2113–2124. 21 indexed citations
4.
Shah, Jatin J., Jonathan L. Kaufman, Jeffrey A. Zonder, et al.. (2017). A Phase 1 and 2 study of Filanesib alone and in combination with low‐dose dexamethasone in relapsed/refractory multiple myeloma. Cancer. 123(23). 4617–4630. 48 indexed citations
5.
Chari, Ajai, Myo Htut, Jeffrey A. Zonder, et al.. (2016). A phase 1 dose‐escalation study of filanesib plus bortezomib and dexamethasone in patients with recurrent/refractory multiple myeloma. Cancer. 122(21). 3327–3335. 33 indexed citations
6.
Nygren, Patrick J., et al.. (2015). Protein Kinase A Opposes the Phosphorylation-dependent Recruitment of Glycogen Synthase Kinase 3β to A-kinase Anchoring Protein 220. Journal of Biological Chemistry. 290(32). 19445–19457. 24 indexed citations
7.
Hernández-García, Susana, Laura San‐Segundo, Teresa Paíno, et al.. (2015). Filanesib (ARRY-520) Demonstrates Potent and Rapid Activity in Preclinical Models of MM, Dependent on Bcl-2 Family Expression, and Synergistic with Dexamethasone and IMiDs. Clinical Lymphoma Myeloma & Leukemia. 15. e213–e214. 1 indexed citations
8.
Logue, Jeremy S., Brian Tunquist, David B. Sacks, et al.. (2011). AKAP220 Protein Organizes Signaling Elements That Impact Cell Migration. Journal of Biological Chemistry. 286(45). 39269–39281. 33 indexed citations
9.
Logue, Jeremy S., et al.. (2011). Anchored Protein Kinase A Recruitment of Active Rac GTPase. Journal of Biological Chemistry. 286(25). 22113–22121. 24 indexed citations
10.
11.
Tunquist, Brian, Richard Woessner, & Duncan Walker. (2010). Mcl-1 Stability Determines Mitotic Cell Fate of Human Multiple Myeloma Tumor Cells Treated with the Kinesin Spindle Protein Inhibitor ARRY-520. Molecular Cancer Therapeutics. 9(7). 2046–2056. 58 indexed citations
12.
Winski, Shannon L., Daniel J. Anderson, Karyn Bouhana, et al.. (2010). 162 MEK162 (ARRY-162), a novel MEK 1/2 inhibitor, inhibits tumor growth regardless of KRas/Raf pathway mutations. European Journal of Cancer Supplements. 8(7). 56–56. 22 indexed citations
13.
Woessner, Richard, Brian Tunquist, Christine Lemieux, et al.. (2009). ARRY-520, a novel KSP inhibitor with potent activity in hematological and taxane-resistant tumor models.. PubMed. 29(11). 4373–80. 51 indexed citations
14.
15.
Tunquist, Brian & James L. Maller. (2003). Under arrest: cytostatic factor (CSF)-mediated metaphase arrest in vertebrate eggs. Genes & Development. 17(6). 683–710. 201 indexed citations
16.
Tunquist, Brian, et al.. (2003). Spindle checkpoint proteins Mad1 and Mad2 are required for cytostatic factor–mediated metaphase arrest. The Journal of Cell Biology. 163(6). 1231–1242. 47 indexed citations
17.
Maller, James L., Markus S. Schwab, Stefan Groß, et al.. (2002). The mechanism of CSF arrest in vertebrate oocytes. Molecular and Cellular Endocrinology. 187(1-2). 173–178. 31 indexed citations
18.
Tunquist, Brian, et al.. (2002). The Spindle Checkpoint Kinase Bub1 and Cyclin E/Cdk2 Both Contribute to the Establishment of Meiotic Metaphase Arrest by Cytostatic Factor. Current Biology. 12(12). 1027–1033. 76 indexed citations
19.
Maller, James L., Markus S. Schwab, B.Tibor Roberts, et al.. (2001). The pathway of MAP kinase mediation of CSF arrest in Xenopus oocytes. Biology of the Cell. 93(1-2). 27–33. 22 indexed citations
20.
Schwab, Markus S., B.Tibor Roberts, Stefan Groß, et al.. (2001). Bub1 is activated by the protein kinase p90 Rsk during Xenopus oocyte maturation. Current Biology. 11(3). 141–150. 87 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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