Michael A. Pleiss

1.9k total citations · 1 hit paper
24 papers, 1.2k citations indexed

About

Michael A. Pleiss is a scholar working on Molecular Biology, Immunology and Allergy and Organic Chemistry. According to data from OpenAlex, Michael A. Pleiss has authored 24 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Immunology and Allergy and 5 papers in Organic Chemistry. Recurrent topics in Michael A. Pleiss's work include Cell Adhesion Molecules Research (6 papers), Analytical Chemistry and Chromatography (4 papers) and Alzheimer's disease research and treatments (3 papers). Michael A. Pleiss is often cited by papers focused on Cell Adhesion Molecules Research (6 papers), Analytical Chemistry and Chromatography (4 papers) and Alzheimer's disease research and treatments (3 papers). Michael A. Pleiss collaborates with scholars based in United States, Canada and Netherlands. Michael A. Pleiss's co-authors include Steven Finkbeiner, Andrey S. Tsvetkov, Jinny S. Wong, Montserrat Arrasate, Jason Miller, Nicholas J. C. King, Meghann Teague Getts, Aaron Daub, Woon Teck Yap and D. Michael Ando and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Biotechnology.

In The Last Decade

Michael A. Pleiss

24 papers receiving 1.2k citations

Hit Papers

Autophagy induction enhances TDP43 turnover and survival ... 2014 2026 2018 2022 2014 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael A. Pleiss United States 13 481 277 273 247 208 24 1.2k
Irina Lonskaya United States 19 642 1.3× 112 0.4× 502 1.8× 329 1.3× 327 1.6× 21 1.5k
Yaacov Hod United States 12 965 2.0× 92 0.3× 301 1.1× 140 0.6× 172 0.8× 14 1.5k
Gillian Greig Canada 25 748 1.6× 114 0.4× 374 1.4× 180 0.7× 129 0.6× 30 2.2k
Stephen K. Youngster United States 22 635 1.3× 126 0.5× 626 2.3× 121 0.5× 108 0.5× 28 1.7k
Emmanuel Normant United States 22 1.3k 2.7× 235 0.8× 111 0.4× 111 0.4× 116 0.6× 50 2.0k
Keiji Shimizu Japan 23 662 1.4× 438 1.6× 167 0.6× 150 0.6× 53 0.3× 117 1.8k
Rebecca L. Maglathlin United States 9 802 1.7× 54 0.2× 129 0.5× 321 1.3× 92 0.4× 11 1.4k
Raphaël Boisgard France 25 661 1.4× 176 0.6× 76 0.3× 100 0.4× 134 0.6× 55 1.7k
Takuya Furuta Japan 22 719 1.5× 183 0.7× 102 0.4× 97 0.4× 60 0.3× 101 1.7k
Yasuhiro Hashimoto Japan 22 722 1.5× 403 1.5× 96 0.4× 42 0.2× 445 2.1× 59 1.6k

Countries citing papers authored by Michael A. Pleiss

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Pleiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael A. Pleiss. 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 Michael A. Pleiss. The network helps show where Michael A. Pleiss may publish in the future.

Co-authorship network of co-authors of Michael A. Pleiss

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Pleiss. A scholar is included among the top collaborators of Michael A. Pleiss 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 Michael A. Pleiss. Michael A. Pleiss 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.
Blasio, Angelo, Jingyi Wang, Dan Wang, et al.. (2017). Novel Small-Molecule Inhibitors of Protein Kinase C Epsilon Reduce Ethanol Consumption in Mice. Biological Psychiatry. 84(3). 193–201. 19 indexed citations
2.
Barmada, Sami J., Andrea Serio, Arpana Arjun, et al.. (2014). Autophagy induction enhances TDP43 turnover and survival in neuronal ALS models. Nature Chemical Biology. 10(8). 677–685. 341 indexed citations breakdown →
3.
Getts, Daniel R., Aaron J. Martin, Derrick McCarthy, et al.. (2012). Microparticles bearing encephalitogenic peptides induce T-cell tolerance and ameliorate experimental autoimmune encephalomyelitis. Nature Biotechnology. 30(12). 1217–1224. 317 indexed citations
4.
Chen, Hung-Kai, Zhaoping Liu, Anke Meyer‐Franke, et al.. (2011). Small Molecule Structure Correctors Abolish Detrimental Effects of Apolipoprotein E4 in Cultured Neurons. Journal of Biological Chemistry. 287(8). 5253–5266. 115 indexed citations
5.
Neitzel, Martin L., Danielle L. Aubele, Jacek Jagodziński, et al.. (2011). Amino-caprolactam γ-secretase inhibitors showing potential for the treatment of Alzheimer’s disease. Bioorganic & Medicinal Chemistry Letters. 21(12). 3715–3720. 4 indexed citations
6.
Chen, Linda, Mark Dreyer, Stephen B. Freedman, et al.. (2011). Discovery of a potent, orally bioavailable pyrimidine VLA-4 antagonist effective in a sheep asthma model. Bioorganic & Medicinal Chemistry Letters. 21(6). 1741–1743. 4 indexed citations
7.
Konradi, Andrei W., Ying‐zi Xu, Albert W. Garofalo, et al.. (2010). Discovery of a novel sulfonamide-pyrazolopiperidine series as potent and Efficacious γ-Secretase Inhibitors. Bioorganic & Medicinal Chemistry Letters. 20(7). 2195–2199. 14 indexed citations
8.
Tsvetkov, Andrey S., Jason Miller, Montserrat Arrasate, et al.. (2010). A small-molecule scaffold induces autophagy in primary neurons and protects against toxicity in a Huntington disease model. Proceedings of the National Academy of Sciences. 107(39). 16982–16987. 203 indexed citations
9.
Neitzel, Martin L., David A. Quincy, Albert W. Garofalo, et al.. (2010). Discovery of sulfonamide–pyrazole γ-secretase inhibitors. Bioorganic & Medicinal Chemistry Letters. 20(7). 2148–2150. 13 indexed citations
10.
Yednock, Ted, Elizabeth K. Messersmith, Michael A. Pleiss, et al.. (2005). Spontaneous remyelination following prolonged inhibition of α4 integrin in chronic EAE. Journal of Neuroimmunology. 167(1-2). 53–63. 12 indexed citations
11.
Huryn, Donna M., Andrei W. Konradi, Susan Ashwell, et al.. (2004). The Identification and Optimization of Orally Efficacious, Small Molecule VLA-4 Antagonists. Current Topics in Medicinal Chemistry. 4(14). 1473–1484. 26 indexed citations
12.
Huryn, Donna M., Susan Ashwell, Andrei W. Konradi, et al.. (2004). Synthesis, characterization and evaluation of pro-drugs of VLA-4 antagonists. Bioorganic & Medicinal Chemistry Letters. 14(7). 1651–1654. 6 indexed citations
13.
Yednock, Ted, Stephen B. Freedman, Elizabeth K. Messersmith, et al.. (2002). Prolonged reversal of chronic experimental allergic encephalomyelitis using a small molecule inhibitor of α4 integrin. Journal of Neuroimmunology. 131(1-2). 147–159. 33 indexed citations
14.
Garofalo, Albert W., James E. Audia, Harry F. Dovey, et al.. (2002). A series of C-Terminal amino alcohol dipeptide Aβ inhibitors. Bioorganic & Medicinal Chemistry Letters. 12(21). 3051–3053. 17 indexed citations
17.
Pleiss, Michael A. & Gary L. Grunewald. (1983). An extension of the f-fragment method for the calculation of hydrophobic constants (log P) of conformationally defined systems. Journal of Medicinal Chemistry. 26(12). 1760–1764. 16 indexed citations
18.
Grunewald, Gary L., Michael A. Pleiss, & Michael Rafferty. (1982). Conformational preferences of dopamine analogues for inhibition of norepinephrine N-methyltransferase. Conformationally defined adrenergic agents. 7. Life Sciences. 31(10). 993–1000. 5 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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