Paul J. Barrett

1.7k total citations · 1 hit paper
17 papers, 1.4k citations indexed

About

Paul J. Barrett is a scholar working on Molecular Biology, Physiology and Nature and Landscape Conservation. According to data from OpenAlex, Paul J. Barrett has authored 17 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Physiology and 5 papers in Nature and Landscape Conservation. Recurrent topics in Paul J. Barrett's work include Alzheimer's disease research and treatments (6 papers), Fish Ecology and Management Studies (5 papers) and Protein Structure and Dynamics (4 papers). Paul J. Barrett is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Fish Ecology and Management Studies (5 papers) and Protein Structure and Dynamics (4 papers). Paul J. Barrett collaborates with scholars based in United States, Germany and Italy. Paul J. Barrett's co-authors include J. Timothy Greenamyre, Charles R. Sanders, Andrew J. Beel, Yuanli Song, Wade D. Van Horn, Eric J. Hustedt, Johanna M. Schafer, Arina Hadziselimovic, Caitlyn W. Barrett and Charleen T. Chu and has published in prestigious journals such as Science, Journal of the American Chemical Society and Biochemistry.

In The Last Decade

Paul J. Barrett

16 papers receiving 1.4k citations

Hit Papers

α-Synuclein binds to TOM2... 2016 2026 2019 2022 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul J. Barrett United States 11 774 587 398 260 164 17 1.4k
Silva Hečimović Croatia 20 818 1.1× 852 1.5× 120 0.3× 226 0.9× 199 1.2× 44 1.6k
Katarzyna Marta Zoltowska United States 17 982 1.3× 556 0.9× 272 0.7× 172 0.7× 190 1.2× 22 1.6k
Gregor P. Lotz United States 16 1.0k 1.3× 372 0.6× 191 0.5× 715 2.8× 180 1.1× 22 1.5k
Nitin D. Mehta United States 17 600 0.8× 708 1.2× 520 1.3× 394 1.5× 89 0.5× 21 1.4k
Yue‐De Yang China 15 777 1.0× 882 1.5× 650 1.6× 258 1.0× 116 0.7× 33 1.8k
Irina N. Gaisina United States 23 931 1.2× 270 0.5× 122 0.3× 211 0.8× 115 0.7× 59 1.6k
Rachel M. Bailey United States 18 1.0k 1.3× 575 1.0× 663 1.7× 333 1.3× 348 2.1× 29 1.9k
Andrea Magrì Italy 22 955 1.2× 445 0.8× 250 0.6× 268 1.0× 125 0.8× 43 1.5k
Mario Nizzari Italy 20 958 1.2× 376 0.6× 110 0.3× 352 1.4× 87 0.5× 51 1.4k
Priyanka Narayan United States 17 691 0.9× 744 1.3× 78 0.2× 169 0.7× 128 0.8× 35 1.4k

Countries citing papers authored by Paul J. Barrett

Since Specialization
Citations

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

Fields of papers citing papers by Paul J. Barrett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul J. Barrett. 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 Paul J. Barrett. The network helps show where Paul J. Barrett may publish in the future.

Co-authorship network of co-authors of Paul J. Barrett

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

All Works

17 of 17 papers shown
1.
Bonar, Scott A., et al.. (2016). Enhancing Hatch Rate and Survival in Laboratory-Reared Hybrid Devils Hole Pupfish through Application of Antibiotics to Eggs and Larvae. North American Journal of Aquaculture. 79(1). 106–114. 7 indexed citations
2.
Maio, Roberto Di, Paul J. Barrett, Eric K. Hoffman, et al.. (2016). α-Synuclein binds to TOM20 and inhibits mitochondrial protein import in Parkinson’s disease. Science Translational Medicine. 8(342). 342ra78–342ra78. 463 indexed citations breakdown →
3.
Bonar, Scott A., et al.. (2016). Design and Testing of a Mesocosm-Scale Habitat for Culturing the Endangered Devils Hole Pupfish. North American Journal of Aquaculture. 78(3). 259–269. 6 indexed citations
4.
Schlebach, Jonathan P., Paul J. Barrett, Charles Day, et al.. (2016). Topologically Diverse Human Membrane Proteins Partition to Liquid-Disordered Domains in Phase-Separated Lipid Vesicles. Biochemistry. 55(7). 985–988. 16 indexed citations
5.
Barrett, Paul J. & J. Timothy Greenamyre. (2015). Post-translational modification of α-synuclein in Parkinson׳s disease. Brain Research. 1628(Pt B). 247–253. 141 indexed citations
6.
Bonar, Scott A., et al.. (2015). Underwater Videography Outperforms Above-Water Videography and In-Person Surveys for Monitoring the Spawning of Devils Hole Pupfish. North American Journal of Fisheries Management. 35(6). 1252–1262. 11 indexed citations
7.
Barrett, Paul J., Chen Jiang, Min‐Kyu Cho, et al.. (2013). The Quiet Renaissance of Protein Nuclear Magnetic Resonance. Biochemistry. 52(8). 1303–1320. 36 indexed citations
8.
Song, Yuanli, et al.. (2013). P2–062: Binding of cholesterol to the C99 domain of APP competes with homodimerzation of the protein. Alzheimer s & Dementia. 9(4S_Part_9). 1 indexed citations
9.
Barrett, Paul J., Yuanli Song, Wade D. Van Horn, et al.. (2012). The Amyloid Precursor Protein Has a Flexible Transmembrane Domain and Binds Cholesterol. Science. 336(6085). 1168–1171. 387 indexed citations
10.
Barrett, Paul J., Daniel Hornburg, Milena Dürrbaum, et al.. (2012). The Backbone Dynamics of the Amyloid Precursor Protein Transmembrane Helix Provides a Rationale for the Sequential Cleavage Mechanism of γ-Secretase. Journal of the American Chemical Society. 135(4). 1317–1329. 65 indexed citations
11.
Barrett, Paul J., Charles R. Sanders, Stephen A. Kaufman, Klaus Michelsen, & John B. Jordan. (2011). NSAID-Based γ-Secretase Modulators Do Not Bind to the Amyloid-β Polypeptide. Biochemistry. 50(47). 10328–10342. 21 indexed citations
12.
Beel, Andrew J., Masayoshi Sakakura, Paul J. Barrett, & Charles R. Sanders. (2010). Direct binding of cholesterol to the amyloid precursor protein: An important interaction in lipid–Alzheimer's disease relationships?. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1801(8). 975–982. 138 indexed citations
13.
Barrett, Paul J.. (2009). Estimating Devils Hole Pupfish Lifestage Ratios Using the Delphi Method. Fisheries. 34(2). 73–79. 9 indexed citations
14.
Beel, Andrew J., Paul J. Barrett, Paul D. Schnier, et al.. (2009). Nonspecificity of Binding of γ-Secretase Modulators to the Amyloid Precursor Protein. Biochemistry. 48(50). 11837–11839. 37 indexed citations
15.
Noble, M.E.M., et al.. (2005). Exploiting structural principles to design cyclin-dependent kinase inhibitors. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1754(1-2). 58–64. 26 indexed citations
16.
Barrett, Paul J. & O. Eugene Maughan. (1994). Habitat Preferences of Introduced Smallmouth Bass in a Central Arizona Stream. North American Journal of Fisheries Management. 14(1). 112–118. 9 indexed citations
17.
Barrett, Paul J.. (1992). Spatial habitat preference of smallmouth bass (Micropterus dolomieui), roundtail chub (Gila robusta), and razorback sucker (Xyaurchen texanus).. International Journal of Radiation Biology and Related Studies in Physics Chemistry and Medicine. 15(6). 549–55. 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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