Daniel Mamott
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Single-cell and spatial transcriptomics
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Pluripotent Stem Cells Research
- Extracellular vesicles in disease
- Bioinformatics and Genomic Networks
- CRISPR and Genetic Engineering
Papers in ⓘ
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- Pluripotent Stem Cells Research 3
- Single-cell and spatial transcriptomics 1
- CRISPR and Genetic Engineering 1
- Planarian Biology and Electrostimulation 1
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- Photoreceptor and optogenetics research 1
- Co-authors
- James A. Thomson (3 shared papers)Li‐Fang Chu (2 shared papers)Christina Kendziorski (2 shared papers)Ron Stewart (2 shared papers)Zhonggang Hou (1 shared paper)Jeea Choi (1 shared paper)Ning Leng (1 shared paper)David Vereide (1 shared paper)
- Journals
- Advanced Healthcare Materials (1 paper)Genome biology (1 paper)Cell Reports (1 paper)Cell chemical biology (1 paper)
- Partner nations
- United States
In The Last Decade
Daniel Mamott
4 papers receiving 381 citations
Peers
Comparison fields: 5 of 52
- Biophysics 44
- Molecular Biology 353
- Cancer Research 62
- Developmental Neuroscience 9
- Biological Psychiatry 4
Countries citing papers authored by Daniel Mamott
This map shows the geographic impact of Daniel Mamott'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 Daniel Mamott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Mamott more than expected).
Fields of papers citing papers by Daniel Mamott
This network shows the impact of papers produced by Daniel Mamott. 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 Daniel Mamott. The network helps show where Daniel Mamott may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Mamott, 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 | 2016 | 302 | |
| 2 | 2019 | 47 | |
| 3 | 2020 | 22 | |
| 4 | 2023 | 14 |
About Daniel Mamott
Daniel Mamott is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Developmental Neuroscience, Immunology and Biomedical Engineering, having authored 4 papers that have together received 385 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (3 papers), interferon and immune responses (1 paper), Single-cell and spatial transcriptomics (1 paper), IL-33, ST2, and ILC Pathways (1 paper), CRISPR and Genetic Engineering (1 paper), Planarian Biology and Electrostimulation (1 paper), Photoreceptor and optogenetics research (1 paper) and 3D Printing in Biomedical Research (1 paper). The work is most often cited by research in Biophysics (44 citations), Molecular Biology (353 citations), Cancer Research (62 citations), Developmental Neuroscience (9 citations) and Biological Psychiatry (4 citations). Daniel Mamott has collaborated with scholars based in United States. Frequent co-authors include James A. Thomson, Li‐Fang Chu, Christina Kendziorski, Ron Stewart, Zhonggang Hou, Jeea Choi, Ning Leng, David Vereide, Jue Zhang and Rhonda Bacher. Their work appears in journals such as Advanced Healthcare Materials, Genome biology, Cell Reports and Cell chemical biology.
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.