Matthew Tegtmeyer
Impact in
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- Cell Image Analysis Techniques
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- Neurogenesis and neuroplasticity mechanisms
Papers in
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- Single-cell and spatial transcriptomics 5
- Pluripotent Stem Cells Research 2
- CRISPR and Genetic Engineering 2
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- Neuroinflammation and Neurodegeneration Mechanisms 3
- Neurofibromatosis and Schwannoma Cases 1
- Co-authors
- Ralda Nehme (7 shared papers)Steven A. McCarroll (5 shared papers)Irene Faravelli (1 shared paper)Rahel Kästli (1 shared paper)Daniela J. Di Bella (1 shared paper)Paola Arlotta (1 shared paper)Sebastiano Trattaro (1 shared paper)Aviv Regev (1 shared paper)
- Journals
- Nature Communications (2 papers)iScience (1 paper)Cell Reports (1 paper)Cell Systems (1 paper)Nature (1 paper)
- Partner nations
- United StatesUnited KingdomFinland
In The Last Decade
Matthew Tegtmeyer
9 papers receiving 119 citations
Peers
Comparison fields: 5 of 43
- Biophysics 17
- Developmental Neuroscience 10
- Cellular and Molecular Neuroscience 25
- Neurology 8
- Molecular Biology 62
Countries citing papers authored by Matthew Tegtmeyer
This map shows the geographic impact of Matthew Tegtmeyer'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 Matthew Tegtmeyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Tegtmeyer more than expected).
Fields of papers citing papers by Matthew Tegtmeyer
This network shows the impact of papers produced by Matthew Tegtmeyer. 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 Matthew Tegtmeyer. The network helps show where Matthew Tegtmeyer may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Tegtmeyer, 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 | 2024 | 45 | |
| 2 | 2024 | 26 | |
| 3 | 2023 | 17 | |
| 4 | 2023 | 10 | |
| 5 | 2025 | 8 | |
| 6 | 2021 | 7 | |
| 7 | 2025 | 4 | |
| 8 | 2025 | 3 | |
| 9 | 2024 | 1 | |
| 10 | 2023 | 0 | |
| 11 | 2026 | 0 |
About Matthew Tegtmeyer
Matthew Tegtmeyer is a scholar working on Molecular Biology, Neurology, Cellular and Molecular Neuroscience, Biophysics and Organic Chemistry, having authored 11 papers that have together received 121 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Pluripotent Stem Cells Research (2 papers), CRISPR and Genetic Engineering (2 papers), Cell Image Analysis Techniques (2 papers), Cancer Mechanisms and Therapy (1 paper), Synthesis of Tetrazole Derivatives (1 paper) and Neurofibromatosis and Schwannoma Cases (1 paper). The work is most often cited by research in Biophysics (17 citations), Developmental Neuroscience (10 citations), Cellular and Molecular Neuroscience (25 citations), Neurology (8 citations) and Molecular Biology (62 citations). Matthew Tegtmeyer has collaborated with scholars based in United States, United Kingdom and Finland. Frequent co-authors include Ralda Nehme, Steven A. McCarroll, Irene Faravelli, Rahel Kästli, Daniela J. Di Bella, Paola Arlotta, Sebastiano Trattaro, Aviv Regev, Kevin Eggan and Tyler Faits. Their work appears in journals such as Nature Communications, iScience, Cell Reports, Cell Systems and Nature.
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.