Tara Gaertner

702 total citations
10 papers, 557 citations indexed

About

Tara Gaertner is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics. According to data from OpenAlex, Tara Gaertner has authored 10 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Computational Theory and Mathematics. Recurrent topics in Tara Gaertner's work include Protein Kinase Regulation and GTPase Signaling (3 papers), Protein Structure and Dynamics (3 papers) and Ion channel regulation and function (2 papers). Tara Gaertner is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (3 papers), Protein Structure and Dynamics (3 papers) and Ion channel regulation and function (2 papers). Tara Gaertner collaborates with scholars based in United States, Canada and Switzerland. Tara Gaertner's co-authors include M. Neal Waxham, John A. Putkey, Yu Tian Wang, Quinn Kleerekoper, Michel Baudry, Wei Xu, Nadège Chéry, Tak Pan Wong, James K Stoops and John M. Koomen and has published in prestigious journals such as Journal of Biological Chemistry, Neuron and Biochemistry.

In The Last Decade

Tara Gaertner

8 papers receiving 546 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tara Gaertner United States 8 393 279 106 51 42 10 557
Maria del Carmen Vitery United States 8 398 1.0× 150 0.5× 74 0.7× 37 0.7× 91 2.2× 8 614
Shengjie Feng United States 11 557 1.4× 242 0.9× 64 0.6× 68 1.3× 21 0.5× 14 834
Chanjuan Xu China 16 509 1.3× 331 1.2× 69 0.7× 24 0.5× 27 0.6× 28 704
Juliane Proft Canada 10 334 0.8× 188 0.7× 50 0.5× 42 0.8× 80 1.9× 17 479
Ryan T. Terry-Lorenzo United States 14 494 1.3× 355 1.3× 286 2.7× 22 0.4× 24 0.6× 20 778
Aline Bréchet Germany 7 473 1.2× 474 1.7× 157 1.5× 18 0.4× 45 1.1× 7 701
Dhrubajyoti Chowdhury United States 13 332 0.8× 288 1.0× 63 0.6× 54 1.1× 29 0.7× 15 510
Christian R. Halaszovich Germany 15 545 1.4× 266 1.0× 95 0.9× 117 2.3× 38 0.9× 22 921
Catrin S. Müller Germany 8 789 2.0× 581 2.1× 168 1.6× 72 1.4× 65 1.5× 14 993
Nikolai I. Kiskin Ukraine 15 507 1.3× 490 1.8× 72 0.7× 27 0.5× 13 0.3× 25 797

Countries citing papers authored by Tara Gaertner

Since Specialization
Citations

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

Fields of papers citing papers by Tara Gaertner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tara Gaertner

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

All Works

10 of 10 papers shown
1.
Taghibiglou, Changiz, Clarrisa A. Bradley, Tara Gaertner, et al.. (2009). Mechanisms involved in cholesterol-induced neuronal insulin resistance. Neuropharmacology. 57(3). 268–276. 26 indexed citations
2.
Forest, Amélie, Matthew T. Swulius, Joyce Ka Yu Tse, et al.. (2008). Role of the N- and C-Lobes of Calmodulin in the Activation of Ca2+/Calmodulin-Dependent Protein Kinase II. Biochemistry. 47(40). 10587–10599. 40 indexed citations
3.
Xu, Wei, Tak Pan Wong, Nadège Chéry, et al.. (2007). Calpain-Mediated mGluR1α Truncation: A Key Step in Excitotoxicity. Neuron. 53(3). 399–412. 141 indexed citations
4.
Putkey, John A., M. Neal Waxham, Tara Gaertner, et al.. (2007). Acidic/IQ Motif Regulator of Calmodulin. Journal of Biological Chemistry. 283(3). 1401–1410. 29 indexed citations
5.
Gaertner, Tara, Steven J. Kolodziej, Dan Wang, et al.. (2004). Comparative Analyses of the Three-dimensional Structures and Enzymatic Properties of α, β, γ, and δ Isoforms of Ca2+-Calmodulin-dependent Protein Kinase II. Journal of Biological Chemistry. 279(13). 12484–12494. 144 indexed citations
6.
Gaertner, Tara, John A. Putkey, & M. Neal Waxham. (2004). RC3/Neurogranin and Ca2+/Calmodulin-dependent Protein Kinase II Produce Opposing Effects on the Affinity of Calmodulin for Calcium. Journal of Biological Chemistry. 279(38). 39374–39382. 79 indexed citations
7.
Kubota, Yoshihisa, Tara Gaertner, John A. Putkey, & M. Neal Waxham. (2004). A novel Monte Carlo simulation for molecular interactions and diffusion in postsynaptic spines. Neurocomputing. 65-66. 595–602. 1 indexed citations
8.
Gaertner, Tara. (2004). A novel mechanism for regulation of calmodulin signaling by RC3. DigtalCommons @ Texas Medical Center Library (Texas Medical Center). 2 indexed citations
9.
Putkey, John A., Quinn Kleerekoper, Tara Gaertner, & M. Neal Waxham. (2003). A New Role for IQ Motif Proteins in Regulating Calmodulin Function. Journal of Biological Chemistry. 278(50). 49667–49670. 87 indexed citations
10.

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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2026