Michael S. Wolfe

18.6k total citations · 4 hit papers
168 papers, 14.5k citations indexed

About

Michael S. Wolfe is a scholar working on Physiology, Molecular Biology and Pharmacology. According to data from OpenAlex, Michael S. Wolfe has authored 168 papers receiving a total of 14.5k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Physiology, 89 papers in Molecular Biology and 27 papers in Pharmacology. Recurrent topics in Michael S. Wolfe's work include Alzheimer's disease research and treatments (98 papers), Cholinesterase and Neurodegenerative Diseases (27 papers) and Computational Drug Discovery Methods (25 papers). Michael S. Wolfe is often cited by papers focused on Alzheimer's disease research and treatments (98 papers), Cholinesterase and Neurodegenerative Diseases (27 papers) and Computational Drug Discovery Methods (25 papers). Michael S. Wolfe collaborates with scholars based in United States, Japan and Belgium. Michael S. Wolfe's co-authors include Dennis J. Selkoe, W. Taylor Kimberly, Beth L. Ostaszewski, Weiming Xia, Thekla S. Diehl, Raphael Kopan, Bart De Strooper, William P. Esler, Wenjuan Ye and Alison Goate and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Michael S. Wolfe

165 papers receiving 14.3k citations

Hit Papers

A presenilin-1-dependent γ-secretase-like protease mediat... 1999 2026 2008 2017 1999 1999 2006 2003 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael S. Wolfe United States 56 8.2k 8.1k 2.6k 2.3k 1.9k 168 14.5k
Wim Annaert Belgium 51 6.6k 0.8× 7.3k 0.9× 1.7k 0.7× 3.3k 1.4× 2.3k 1.2× 141 13.1k
Koji Takio Japan 76 4.1k 0.5× 13.4k 1.7× 794 0.3× 3.1k 1.3× 2.3k 1.2× 196 20.9k
Gloria Lee United States 56 5.2k 0.6× 6.2k 0.8× 901 0.3× 2.6k 1.1× 2.4k 1.3× 127 12.7k
Anthony H. Futerman Israel 73 6.4k 0.8× 12.8k 1.6× 773 0.3× 5.3k 2.3× 962 0.5× 282 18.3k
Peter J. Parker United Kingdom 95 3.0k 0.4× 25.3k 3.1× 972 0.4× 7.6k 3.3× 3.0k 1.6× 406 33.7k
Kun Ping Lu United States 74 2.8k 0.3× 17.4k 2.1× 697 0.3× 2.6k 1.1× 2.1k 1.1× 208 21.0k
Hiroyoshi Hidaka Japan 59 1.9k 0.2× 9.3k 1.1× 822 0.3× 1.7k 0.7× 2.6k 1.3× 326 14.3k
Per Westermark Sweden 80 9.2k 1.1× 15.6k 1.9× 431 0.2× 3.1k 1.3× 1.3k 0.7× 372 23.1k
Rony Seger Israel 70 1.3k 0.2× 14.9k 1.8× 778 0.3× 3.1k 1.3× 2.7k 1.4× 206 22.2k
Rob Leurs Netherlands 71 2.3k 0.3× 10.9k 1.3× 813 0.3× 294 0.1× 3.8k 2.0× 443 19.1k

Countries citing papers authored by Michael S. Wolfe

Since Specialization
Citations

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

Fields of papers citing papers by Michael S. Wolfe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael S. Wolfe

This figure shows the co-authorship network connecting the top 25 collaborators of Michael S. Wolfe. A scholar is included among the top collaborators of Michael S. Wolfe 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 S. Wolfe. Michael S. Wolfe 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
2.
Wolfe, Michael S.. (2025). Presenilin, γ-Secretase, and the Search for Pathogenic Triggers of Alzheimer’s Disease. Biochemistry. 64(8). 1662–1672. 5 indexed citations
3.
Wolfe, Michael S., et al.. (2025). Effects of Transmembrane Phenylalanine Residues on γ-Secretase-Mediated Notch-1 Proteolysis. ACS Chemical Neuroscience. 16(5). 844–855. 2 indexed citations
4.
Zhou, Rui, Masato Maesako, N. Hung, et al.. (2024). Familial Alzheimer mutations stabilize synaptotoxic γ-secretase-substrate complexes. Cell Reports. 43(2). 113761–113761. 15 indexed citations
5.
Wolfe, Michael S., et al.. (2024). Automation of quantum dot measurement analysis via explainable machine learning. Machine Learning Science and Technology. 6(1). 15006–15006. 1 indexed citations
6.
Williams, Emily L., et al.. (2024). Alzheimer-mutant γ-secretase complexes stall amyloid β-peptide production. eLife. 13. 3 indexed citations
7.
Aron, Liviu, Chenxi Qiu, M H Liang, et al.. (2023). A neurodegeneration checkpoint mediated by REST protects against the onset of Alzheimer’s disease. Nature Communications. 14(1). 7030–7030. 4 indexed citations
8.
Bhattarai, Apurba, Hung D. Nguyen, Jinan Wang, et al.. (2022). Mechanism of Tripeptide Trimming of Amyloid β-Peptide 49 by γ-Secretase. Journal of the American Chemical Society. 144(14). 6215–6226. 22 indexed citations
9.
Castro, Manuel, et al.. (2022). Verteporfin is a substrate-selective γ-secretase inhibitor that binds the amyloid precursor protein transmembrane domain. Journal of Biological Chemistry. 298(4). 101792–101792. 10 indexed citations
10.
Williams, Todd D., et al.. (2021). Familial Alzheimer’s disease mutations in amyloid protein precursor alter proteolysis by γ-secretase to increase amyloid β-peptides of ≥45 residues. Journal of Biological Chemistry. 296. 100281–100281. 41 indexed citations
11.
Wolfe, Michael S.. (2019). Substrate recognition and processing by γ-secretase. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1862(1). 183016–183016. 31 indexed citations
12.
Bhattarai, Sanjay, et al.. (2019). Designed Helical Peptides as Functional Probes for γ-Secretase. Biochemistry. 58(44). 4398–4407. 5 indexed citations
13.
Montagna, Daniel R., et al.. (2016). The amyloid-beta forming tripeptide cleavage mechanism of γ-secretase. eLife. 5. 125 indexed citations
14.
Wolfe, Michael S.. (2011). γ‐Secretase inhibitors and modulators for Alzheimer’s disease. Journal of Neurochemistry. 120(s1). 89–98. 107 indexed citations
15.
Osenkowski, Pamela, Hua Li, Wenjuan Ye, et al.. (2008). Cryoelectron Microscopy Structure of Purified γ-Secretase at 12 Å Resolution. Journal of Molecular Biology. 385(2). 642–652. 93 indexed citations
16.
17.
Campbell, William A., et al.. (2003). Presenilin endoproteolysis mediated by an aspartyl protease activity pharmacologically distinct from γ‐secretase. Journal of Neurochemistry. 85(6). 1563–1574. 32 indexed citations
18.
Esler, William P., W. Taylor Kimberly, Beth L. Ostaszewski, et al.. (2000). Transition-state analogue inhibitors of γ-secretase bind directly to presenilin-1. Nature Cell Biology. 2(7). 428–434. 435 indexed citations
19.
Wolfe, Michael S.. (1997). N-Benzoyl-4-(dimethylamino)pyridinium Chloride: Isolation and Use for the Direct Benzoylation of Alcohols. Synthetic Communications. 27(17). 2975–2984. 13 indexed citations
20.
Wolfe, Michael S. & Rogers E. Harry‐O'kuru. (1995). A concise synthesis of 2′-c-methylribonucleosides. Tetrahedron Letters. 36(42). 7611–7614. 14 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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