Thomas Abbott

664 total citations
9 papers, 228 citations indexed

About

Thomas Abbott is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Thomas Abbott has authored 9 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Cell Biology. Recurrent topics in Thomas Abbott's work include Neuroscience and Neuropharmacology Research (3 papers), Stress Responses and Cortisol (2 papers) and Protein Kinase Regulation and GTPase Signaling (2 papers). Thomas Abbott is often cited by papers focused on Neuroscience and Neuropharmacology Research (3 papers), Stress Responses and Cortisol (2 papers) and Protein Kinase Regulation and GTPase Signaling (2 papers). Thomas Abbott collaborates with scholars based in United States, Qatar and United Kingdom. Thomas Abbott's co-authors include Christopher M. Colangelo, Lisa Chung, TuKiet T. Lam, Kathryn L. Stone, Angus C. Nairn, Lan Wei, Arie Kaffman, Hao Jin, Erol E. Gulcicek and Robert R. Kitchen and has published in prestigious journals such as Journal of Neuroscience, Molecular Biology of the Cell and PROTEOMICS.

In The Last Decade

Thomas Abbott

9 papers receiving 227 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Abbott United States 9 88 78 58 43 28 9 228
Joshua L. Smalley United States 9 152 1.7× 116 1.5× 40 0.7× 27 0.6× 11 0.4× 16 256
Bo Hao China 11 163 1.9× 81 1.0× 48 0.8× 39 0.9× 17 0.6× 21 348
Xiaoxia Li United States 7 137 1.6× 113 1.4× 32 0.6× 26 0.6× 31 1.1× 11 323
Il Bin Kim South Korea 9 152 1.7× 35 0.4× 37 0.6× 45 1.0× 21 0.8× 16 330
Pasquale Manzerra United States 5 155 1.8× 160 2.1× 24 0.4× 47 1.1× 36 1.3× 5 335
Inès Khadimallah Switzerland 9 118 1.3× 44 0.6× 36 0.6× 28 0.7× 9 0.3× 16 270
Dayton J. Goodell United States 10 184 2.1× 197 2.5× 30 0.5× 43 1.0× 14 0.5× 13 330
Yusuke Wakabayashi Japan 7 130 1.5× 34 0.4× 101 1.7× 14 0.3× 37 1.3× 16 343
Yoshie Kikuchi Japan 9 48 0.5× 38 0.5× 39 0.7× 28 0.7× 24 0.9× 19 196
Christian G. Bouwkamp Netherlands 6 71 0.8× 61 0.8× 36 0.6× 55 1.3× 9 0.3× 9 249

Countries citing papers authored by Thomas Abbott

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Abbott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Abbott

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

All Works

9 of 9 papers shown
1.
Williams, Kenneth R., Christopher M. Colangelo, Lin Hou, et al.. (2017). Use of a Targeted Urine Proteome Assay (TUPA) to identify protein biomarkers of delayed recovery after kidney transplant. PROTEOMICS - CLINICAL APPLICATIONS. 11(7-8). 11 indexed citations
2.
Miller, Megan B., Yan Yan, Kazuya Machida, et al.. (2017). Brain Region and Isoform-Specific Phosphorylation Alters Kalirin SH2 Domain Interaction Sites and Calpain Sensitivity. ACS Chemical Neuroscience. 8(7). 1554–1569. 11 indexed citations
3.
Rich, Matthew T., Thomas Abbott, Lisa Chung, et al.. (2016). Phosphoproteomic Analysis Reveals a Novel Mechanism of CaMKII  Regulation Inversely Induced by Cocaine Memory Extinction versus Reconsolidation. Journal of Neuroscience. 36(29). 7613–7627. 40 indexed citations
4.
Wei, Lan, Hao Jin, Thomas Abbott, et al.. (2015). Early-Life Stress Perturbs Key Cellular Programs in the Developing Mouse Hippocampus. Developmental Neuroscience. 37(6). 476–488. 39 indexed citations
5.
Cantley, Lloyd G., Christopher M. Colangelo, Kathryn L. Stone, et al.. (2015). Development of a Targeted Urine Proteome Assay for kidney diseases. PROTEOMICS - CLINICAL APPLICATIONS. 10(1). 58–74. 15 indexed citations
6.
Ma, Xin‐Ming, Megan B. Miller, Yanping Wang, et al.. (2014). Nonenzymatic domains of Kalirin7 contribute to spine morphogenesis through interactions with phosphoinositides and Abl. Molecular Biology of the Cell. 25(9). 1458–1471. 24 indexed citations
7.
Cates, Hannah M., Madeline L. Pfau, Elizabeth A. Heller, et al.. (2014). Threonine 149 Phosphorylation Enhances ΔFosB Transcriptional Activity to Control Psychomotor Responses to Cocaine. Journal of Neuroscience. 34(34). 11461–11469. 21 indexed citations
8.
Colangelo, Christopher M., Gordana Ivosev, Lisa Chung, et al.. (2014). Development of a highly automated and multiplexed targeted proteome pipeline and assay for 112 rat brain synaptic proteins. PROTEOMICS. 15(7). 1202–1214. 15 indexed citations
9.
Bordner, Kelly A., Becky C. Carlyle, Alvaro Duque, et al.. (2011). Functional Genomic and Proteomic Analysis Reveals Disruption of Myelin-Related Genes and Translation in a Mouse Model of Early Life Neglect. Frontiers in Psychiatry. 2. 18–18. 52 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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2026