Thomas Moerman
Impact in
- Aging top 2%
- Immunology top 2%
- Immune cells in cancer
- Immune Cell Function and Interaction
Papers in
- Aging 1
- Genetics, Aging, and Longevity in Model Organisms 1
- Co-authors
- Stein Aerts (2 shared papers)Jan A Aerts (2 shared papers)Carmen Bravo González‐Blas (2 shared papers)Sara Aibar (2 shared papers)Jasper Wouters (1 shared paper)Joost van den Oord (1 shared paper)Hana Imrichová (1 shared paper)Vân Anh Huynh‐Thu (1 shared paper)
- Journals
- Nature Methods (1 paper)Analytical and Bioanalytical Chemistry (1 paper)Bioinformatics (1 paper)Cell (1 paper)The Prague Bulletin of Mathematical Linguistics (1 paper)
- Partner nations
- BelgiumUnited States
In The Last Decade
Thomas Moerman
4 papers receiving 5.0k citations
Thomas Moerman's Hit Papers
Peers
Comparison fields: 5 of 120
- Aging 127
- Immunology 1.2k
- Molecular Biology 2.8k
- Cancer Research 546
- Biophysics 194
Countries citing papers authored by Thomas Moerman
This map shows the geographic impact of Thomas Moerman'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 Thomas Moerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Moerman more than expected).
Fields of papers citing papers by Thomas Moerman
This network shows the impact of papers produced by Thomas Moerman. 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 Thomas Moerman. The network helps show where Thomas Moerman may publish in the future.
Co-authors
The 21 scholars most cited alongside Thomas Moerman, 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 | SCENIC: single-cell regulatory network inference and clustering Hit paper breakdown → | 2017 | 4033 |
| 2 | A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain Hit paper breakdown → | 2018 | 536 |
| 3 | GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks Hit paper breakdown → | 2018 | 378 |
| 4 | 2021 | 28 | |
| 5 | 2024 | 0 |
About Thomas Moerman
Thomas Moerman is a scholar working on Aging, Biophysics, Molecular Biology, Cellular and Molecular Neuroscience and Information Systems, having authored 5 papers that have together received 5.0k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (2 papers), Advanced Chemical Sensor Technologies (1 paper), Web Data Mining and Analysis (1 paper), Gene Regulatory Network Analysis (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper), Genetics, Aging, and Longevity in Model Organisms (1 paper), Topic Modeling (1 paper) and Neurobiology and Insect Physiology Research (1 paper). The work is most often cited by research in Aging (127 citations), Immunology (1.2k citations), Molecular Biology (2.8k citations), Cancer Research (546 citations) and Biophysics (194 citations). Thomas Moerman has collaborated with scholars based in Belgium and United States. Frequent co-authors include Stein Aerts, Jan A Aerts, Carmen Bravo González‐Blas, Sara Aibar, Jasper Wouters, Joost van den Oord, Hana Imrichová, Vân Anh Huynh‐Thu, Jean‐Christophe Marine and Pierre Geurts. Their work appears in journals such as Nature Methods, Analytical and Bioanalytical Chemistry, Bioinformatics, Cell and The Prague Bulletin of Mathematical Linguistics.
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.