Thomas Moerman
Impact in
- Immunology top 5%
- Immune cells in cancer
- Immune Cell Function and Interaction
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
Papers in
-
- Metabolomics and Mass Spectrometry Studies 1
- Gene Regulatory Network Analysis 1
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- Web Data Mining and Analysis 1
- Co-authors
- Jan Aerts (2 shared papers)Stein Aerts (2 shared papers)Sara Aibar (2 shared papers)Carmen Bravo González‐Blas (2 shared papers)Vân Anh Huynh‐Thu (1 shared paper)Hana Imrichová (1 shared paper)Zeynep Kalender Atak (1 shared paper)Pierre Geurts (1 shared paper)
- Journals
- Bioinformatics (1 paper)Analytical and Bioanalytical Chemistry (1 paper)Nature Methods (1 paper)The Prague Bulletin of Mathematical Linguistics (1 paper)
- Partner nations
- BelgiumUnited States
In The Last Decade
Thomas Moerman
3 papers receiving 3.7k citations
Thomas Moerman's Hit Papers
Peers
Comparison fields: 5 of 112
- Immunology 858
- Cancer Research 461
- Molecular Biology 2.2k
- Biophysics 142
- Neurology 167
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 | 3357 |
| 2 | GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks Hit paper breakdown → | 2018 | 323 |
| 3 | 2021 | 26 | |
| 4 | 2024 | 0 |
About Thomas Moerman
Thomas Moerman is a scholar working on Molecular Biology, Information Systems, Ecology, Artificial Intelligence and Biophysics, having authored 4 papers that have together received 3.7k indexed citations. Recurring topics across this work include Isotope Analysis in Ecology (1 paper), Web Data Mining and Analysis (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper), Natural Language Processing Techniques (1 paper), Advanced Chemical Sensor Technologies (1 paper), Gene Regulatory Network Analysis (1 paper), Topic Modeling (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Immunology (858 citations), Cancer Research (461 citations), Molecular Biology (2.2k citations), Biophysics (142 citations) and Neurology (167 citations). Thomas Moerman has collaborated with scholars based in Belgium and United States. Frequent co-authors include Jan Aerts, Stein Aerts, Sara Aibar, Carmen Bravo González‐Blas, Vân Anh Huynh‐Thu, Hana Imrichová, Zeynep Kalender Atak, Pierre Geurts, Gert Hulselmans and Jean‐Christophe Marine. Their work appears in journals such as Bioinformatics, Analytical and Bioanalytical Chemistry, Nature Methods 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.