Jan Aerts
Impact in
- Molecular Biology top 2%
- Single-cell and spatial transcriptomics
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Immunology top 2%
- Immune cells in cancer
- Immune Cell Function and Interaction
Papers in
-
- Genomics and Phylogenetic Studies 12
- Bioinformatics and Genomic Networks 9
- Gene expression and cancer classification 6
- Biomedical Text Mining and Ontologies 4
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- Data Visualization and Analytics 12
- Co-authors
- Sara Aibar (2 shared papers)Thomas Moerman (2 shared papers)Stein Aerts (2 shared papers)Carmen Bravo González‐Blas (2 shared papers)Jasper Wouters (1 shared paper)Florian Rambow (1 shared paper)Vân Anh Huynh‐Thu (1 shared paper)Pierre Geurts (1 shared paper)
- Journals
- Bioinformatics (6 papers)BMC Bioinformatics (4 papers)PeerJ Computer Science (3 papers)Nature Methods (2 papers)BMC Genetics (2 papers)
- Partner nations
- BelgiumUnited KingdomUnited States
In The Last Decade
Jan Aerts
65 papers receiving 5.8k citations
Jan Aerts's Hit Papers
Peers
Comparison fields: 5 of 183
- Molecular Biology 3.1k
- Immunology 922
- Cancer Research 607
- Genetics 827
- Biophysics 163
Countries citing papers authored by Jan Aerts
This map shows the geographic impact of Jan Aerts'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 Jan Aerts with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Aerts more than expected).
Fields of papers citing papers by Jan Aerts
This network shows the impact of papers produced by Jan Aerts. 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 Jan Aerts. The network helps show where Jan Aerts may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Aerts, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | SCENIC: single-cell regulatory network inference and clustering Hit paper breakdown → | 2017 | 3357 |
| 2 | Using graph theory to analyze biological networks Hit paper breakdown → | 2011 | 525 |
| 3 | GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks Hit paper breakdown → | 2018 | 323 |
| 4 | Encyclopedia of Life Sciences | 2009 | 208 |
| 5 | 2007 | 201 | |
| 6 | 2013 | 129 | |
| 7 | 2010 | 122 | |
| 8 | 2008 | 103 | |
| 9 | 2012 | 90 | |
| 10 | 2016 | 77 | |
| 11 | 2019 | 60 | |
| 12 | 2014 | 60 | |
| 13 | 2011 | 45 | |
| 14 | 2012 | 40 | |
| 15 | 2007 | 38 | |
| 16 | 2013 | 38 | |
| 17 | 2009 | 37 | |
| 18 | 2007 | 32 | |
| 19 | 2009 | 31 | |
| 20 | 2012 | 28 |
About Jan Aerts
Jan Aerts is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Genetics, Artificial Intelligence and Plant Science, having authored 69 papers that have together received 5.8k indexed citations. Recurring topics across this work include Data Visualization and Analytics (12 papers), Genomics and Phylogenetic Studies (12 papers), Bioinformatics and Genomic Networks (9 papers), Gene expression and cancer classification (6 papers), Genomics and Rare Diseases (6 papers), Cell Image Analysis Techniques (4 papers), Chromosomal and Genetic Variations (4 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Molecular Biology (3.1k citations), Immunology (922 citations), Cancer Research (607 citations), Genetics (827 citations) and Biophysics (163 citations). Jan Aerts has collaborated with scholars based in Belgium, United Kingdom and United States. Frequent co-authors include Sara Aibar, Thomas Moerman, Stein Aerts, Carmen Bravo González‐Blas, Jasper Wouters, Florian Rambow, Vân Anh Huynh‐Thu, Pierre Geurts, Gert Hulselmans and Joost van den Oord. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, PeerJ Computer Science, Nature Methods and BMC Genetics.
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.