Kerri Spilker

491 total citations
11 papers, 327 citations indexed

About

Kerri Spilker is a scholar working on Molecular Biology, Cell Biology and Aging. According to data from OpenAlex, Kerri Spilker has authored 11 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Cell Biology and 5 papers in Aging. Recurrent topics in Kerri Spilker's work include Genetics, Aging, and Longevity in Model Organisms (5 papers), Microtubule and mitosis dynamics (3 papers) and Photosynthetic Processes and Mechanisms (2 papers). Kerri Spilker is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (5 papers), Microtubule and mitosis dynamics (3 papers) and Photosynthetic Processes and Mechanisms (2 papers). Kerri Spilker collaborates with scholars based in United States and Germany. Kerri Spilker's co-authors include Kang Shen, Miriam B. Goodman, Juan G. Cueva, John Perrino, Claire E. Richardson, Michael Krieg, Daniel Cremers, Alexander R. Dunn, Richard D. Fetter and Jan Stühmer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Immunology and PLoS ONE.

In The Last Decade

Kerri Spilker

11 papers receiving 322 citations

Peers

Kerri Spilker

MB

CB

CMN

AGING

PHYSI

Muriel Desbois United States

Susan G. Fox United States

Bryan W. Vought United States

James Jiayuan Tong United States

Emilia Komulainen United Kingdom

Tim Davies United Kingdom

Aline Ricarda Dörrbaum Germany

Kyoko Chiba Japan

Eshrat Babaie Norway

Alessio Vagnoni United Kingdom

Muriel Desbois United States

Kerri Spilker

167 ×0.9

MB

77 ×0.6

CB

89 ×1.2

CMN

118 ×2.0

AGING

28 ×0.7

PHYSI

Citations per year, relative to Kerri Spilker Kerri Spilker (= 1×) peers Muriel Desbois

Countries citing papers authored by Kerri Spilker

Since Specialization

Citations

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

Fields of papers citing papers by Kerri Spilker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kerri Spilker

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

All Works

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11 of 11 papers shown

1.

Wemlinger, Scott M., Chelsea R. Parker Harp, Bo Yu, et al.. (2022). Preclinical Analysis of Candidate Anti-Human CD79 Therapeutic Antibodies Using a Humanized CD79 Mouse Model. The Journal of Immunology. 208(7). 1566–1584. 8 indexed citations

2.

Marcotte, D.J., Kerri Spilker, Dingyi Wen, et al.. (2020). The crystal structure of the catalytic domain of tau tubulin kinase 2 in complex with a small-molecule inhibitor. Acta Crystallographica Section F Structural Biology Communications. 76(3). 103–108. 4 indexed citations

3.

Peterson, Emily A., Joseph C. Santoro, Istvan Enyedy, et al.. (2020). Human PLD structures enable drug design and characterization of isoenzyme selectivity. Nature Chemical Biology. 16(4). 391–399. 23 indexed citations

4.

Xin, Zhili, J. Howard Jones, Istvan Enyedy, et al.. (2019). Rational Design and Optimization of a Novel Class of Macrocyclic Apoptosis Signal-Regulating Kinase 1 Inhibitors. Journal of Medicinal Chemistry. 62(23). 10740–10756. 25 indexed citations

5.

Krieg, Michael, Juan G. Cueva, Richard D. Fetter, et al.. (2017). Tau Like Proteins Reduce Torque Generation in Microtubule Bundles. Biophysical Journal. 112(3). 29a–30a. 1 indexed citations

6.

Krieg, Michael, Jan Stühmer, Juan G. Cueva, et al.. (2017). Genetic defects in β-spectrin and tau sensitize C. elegans axons to movement-induced damage via torque-tension coupling. eLife. 6. 87 indexed citations

7.

Spilker, Kerri, et al.. (2014). MTM-6, a Phosphoinositide Phosphatase, is Required to Promote Synapse Formation in Caenorhabditis elegans. PLoS ONE. 9(12). e114501–e114501. 1 indexed citations

8.

Richardson, Claire E., Kerri Spilker, Juan G. Cueva, et al.. (2014). PTRN-1, a microtubule minus end-binding CAMSAP homolog, promotes microtubule function in Caenorhabditis elegans neurons. eLife. 3. e01498–e01498. 74 indexed citations

9.

Spilker, Kerri, et al.. (2012). Caenorhabditis elegans Muscleblind homolog mbl-1 functions in neurons to regulate synapse formation. Neural Development. 7(1). 7–7. 28 indexed citations

10.

Friedel, Roland H., Andrew Plump, Xiaowei Lu, et al.. (2005). Gene targeting using a promoterless gene trap vector (“targeted trapping”) is an efficient method to mutate a large fraction of genes. Proceedings of the National Academy of Sciences. 102(37). 13188–13193. 75 indexed citations

11.

Vergara, Leoncio, et al.. (1999). Functional hemi-gap junctions in polarized epithelial cells from human renal proximal tubule. 2. 73015. 1 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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