Frank M. LaFerla
- Biological Psychiatry top 0.02%
- Tryptophan and brain disorders 23
- Neurology top 0.01%
- Neuroinflammation and Neurodegeneration Mechanisms 42
- Physiology top 0.01%
- Alzheimer's disease research and treatments 192
- Cellular and Molecular Neuroscience top 0.05%
- Neuroscience and Neuropharmacology Research 47
- Nuclear Receptors and Signaling 27
- Developmental Neuroscience top 0.1%
- Neurogenesis and neuroplasticity mechanisms 16
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- Cholinesterase and Neurodegenerative Diseases 51
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- Computational Drug Discovery Methods 19
- Co-authors
- Salvatore OddoHenry QuerfurthKim N. GreenAntonella CaccamoMasashi KitazawaLauren M. BillingsMark P. MattsonMathew Blurton‐Jones
- Journals
- New England Journal of Medicine (2 papers)Proceedings of the National Academy of Sciences (8 papers)Journal of the American Chemical Society (1 paper)
- Partner nations
- United StatesSpainCanada
In The Last Decade
Frank M. LaFerla
245 papers receiving 36.2k citations
Hit Papers
Peers
Comparison fields: 5 of 172
- Biological Psychiatry 3.4k
- Neurology 8.0k
- Physiology 23.2k
- Cellular and Molecular Neuroscience 10.1k
- Developmental Neuroscience 2.2k
Countries citing papers authored by Frank M. LaFerla
This map shows the geographic impact of Frank M. LaFerla'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 Frank M. LaFerla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank M. LaFerla more than expected).
Fields of papers citing papers by Frank M. LaFerla
This network shows the impact of papers produced by Frank M. LaFerla. 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 Frank M. LaFerla. The network helps show where Frank M. LaFerla may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Frank M. LaFerla, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2021 | 4 | |
| 3 | 2020 | 50 | |
| 4 | 2020 | 62 | |
| 5 | 2019 | 22 | |
| 6 | 2018 | 42 | |
| 7 | 2018 | 18 | |
| 8 | 2017 | 113 | |
| 9 | 2015 | 71 | |
| 10 | 2015 | 65 | |
| 11 | 2013 | 82 | |
| 12 | 2012 | 42 | |
| 13 | 2011 | 62 | |
| 14 | 2009 | 232 | |
| 15 | 2008 | 319 | |
| 16 | 2008 | 270 | |
| 17 | 2004 | 405 | |
| 18 | 2004 | 97 | |
| 19 | 2004 | 43 | |
| 20 | 2004 | 365 |
About Frank M. LaFerla
Frank M. LaFerla is a scholar working on Biological Psychiatry, Physiology and Neurology, having authored 248 papers that have together received 36.7k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (192 papers), Cholinesterase and Neurodegenerative Diseases (51 papers), Neuroscience and Neuropharmacology Research (47 papers), Neuroinflammation and Neurodegeneration Mechanisms (42 papers), Nuclear Receptors and Signaling (27 papers), Tryptophan and brain disorders (23 papers), Computational Drug Discovery Methods (19 papers) and Neurogenesis and neuroplasticity mechanisms (16 papers). The work is most often cited by research in Biological Psychiatry (3.4k citations), Neurology (8.0k citations) and Physiology (23.2k citations). Frank M. LaFerla has collaborated with scholars based in United States, Spain and Canada. Frequent co-authors include Salvatore Oddo, Henry Querfurth, Kim N. Green, Antonella Caccamo, Masashi Kitazawa, Lauren M. Billings, Mark P. Mattson, Mathew Blurton‐Jones, Yama Akbari and James L. McGaugh. Their work appears in journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.