Maya K. Weigel
Impact in
- Neurology top 2%
- Neuroinflammation and Neurodegeneration Mechanisms
- Amyotrophic Lateral Sclerosis Research
- Developmental Neuroscience top 5%
- Neurogenesis and neuroplasticity mechanisms
Papers in
-
- Neuroinflammation and Neurodegeneration Mechanisms 5
- Neurological Disease Mechanisms and Treatments 1
- Amyotrophic Lateral Sclerosis Research 1
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- Immune cells in cancer 2
- Galectins and Cancer Biology 1
- Co-authors
- Shane A. Liddelow (4 shared papers)Kevin A. Guttenplan (3 shared papers)Aaron D. Gitler (2 shared papers)Ben A. Barres (2 shared papers)Drew Adler (2 shared papers)Alexandra E. Münch (3 shared papers)Julien Couthouis (1 shared paper)Prageeth R. Wijewardhane (1 shared paper)
- Journals
- Nature Communications (1 paper)Nature (1 paper)Developmental Neurobiology (1 paper)Journal of Neurochemistry (1 paper)Frontiers in Molecular Neuroscience (1 paper)
- Partner nations
- United StatesBelgiumGermany
In The Last Decade
Maya K. Weigel
5 papers receiving 739 citations
Maya K. Weigel's Hit Papers
Peers
Comparison fields: 5 of 74
- Neurology 421
- Developmental Neuroscience 103
- Biological Psychiatry 47
- Neurology 137
- Cellular and Molecular Neuroscience 152
Countries citing papers authored by Maya K. Weigel
This map shows the geographic impact of Maya K. Weigel'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 Maya K. Weigel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya K. Weigel more than expected).
Fields of papers citing papers by Maya K. Weigel
This network shows the impact of papers produced by Maya K. Weigel. 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 Maya K. Weigel. The network helps show where Maya K. Weigel may publish in the future.
Co-authors
The 25 scholars most cited alongside Maya K. Weigel, 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 | Neurotoxic reactive astrocytes induce cell death via saturated lipids Hit paper breakdown → | 2021 | 361 |
| 2 | 2020 | 187 | |
| 3 | 2020 | 154 | |
| 4 | 2020 | 29 | |
| 5 | 2024 | 11 | |
| 6 | 2024 | 0 |
About Maya K. Weigel
Maya K. Weigel is a scholar working on Neurology, Immunology, Molecular Biology, Neurology and Physiology, having authored 6 papers that have together received 742 indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Alzheimer's disease research and treatments (2 papers), Immune cells in cancer (2 papers), Galectins and Cancer Biology (1 paper), Neurological Disease Mechanisms and Treatments (1 paper), Glycosylation and Glycoproteins Research (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper) and Amyotrophic Lateral Sclerosis Research (1 paper). The work is most often cited by research in Neurology (421 citations), Developmental Neuroscience (103 citations), Biological Psychiatry (47 citations), Neurology (137 citations) and Cellular and Molecular Neuroscience (152 citations). Maya K. Weigel has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Shane A. Liddelow, Kevin A. Guttenplan, Aaron D. Gitler, Ben A. Barres, Drew Adler, Alexandra E. Münch, Julien Couthouis, Prageeth R. Wijewardhane, Jonathan Fine and Gaurav Chopra. Their work appears in journals such as Nature Communications, Nature, Developmental Neurobiology, Journal of Neurochemistry and Frontiers in Molecular Neuroscience.
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.