Patrick E. Meyer
Impact in
- Molecular Biology top 10%
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Statistics and Probability top 5%
- Statistical Methods and Inference
Papers in
-
- Gene Regulatory Network Analysis 6
- Gene expression and cancer classification 2
- Bioinformatics and Genomic Networks 1
- Co-authors
- Gianluca Bontempi (7 shared papers)Frédéric Lafitte (2 shared papers)Kevin Kontos (2 shared papers)Colas Schretter (1 shared paper)Catharina Olsen (2 shared papers)Daniel Marbach (1 shared paper)Sushmita Mimi Roy (1 shared paper)
- Journals
- IEEE Journal of Selected Topics in Signal Processing (1 paper)BMC Bioinformatics (1 paper)Lecture notes in computer science (1 paper)ORBi (University of Liège) (1 paper)Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (2 papers)
- Partner nations
- BelgiumUnited StatesSwitzerland
In The Last Decade
Patrick E. Meyer
8 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 742
- Statistics and Probability 63
- Artificial Intelligence 150
- Computer Vision and Pattern Recognition 66
- Aging 3
Countries citing papers authored by Patrick E. Meyer
This map shows the geographic impact of Patrick E. Meyer'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 Patrick E. Meyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick E. Meyer more than expected).
Fields of papers citing papers by Patrick E. Meyer
This network shows the impact of papers produced by Patrick E. Meyer. 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 Patrick E. Meyer. The network helps show where Patrick E. Meyer may publish in the future.
Co-authors
The 7 scholars most cited alongside Patrick E. Meyer, 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 | 2008 | 404 | |
| 2 | 2007 | 313 | |
| 3 | 2008 | 224 | |
| 4 | 2009 | 61 | |
| 5 | Information-Theoretic Inference of Gene Networks Using Backward Elimination | 2010 | 34 |
| 6 | Causal filter selection in microarray data | 2010 | 30 |
| 7 | 2007 | 11 | |
| 8 | On the impact of entropy estimator in transcriptional regulatory network inference | 2008 | 11 |
About Patrick E. Meyer
Patrick E. Meyer is a scholar working on Molecular Biology, Nuclear Energy and Engineering, Waste Management and Disposal, Infectious Diseases and Organic Chemistry, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (6 papers), Gene expression and cancer classification (2 papers) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Molecular Biology (742 citations), Statistics and Probability (63 citations), Artificial Intelligence (150 citations), Computer Vision and Pattern Recognition (66 citations) and Aging (3 citations). Patrick E. Meyer has collaborated with scholars based in Belgium, United States and Switzerland. Frequent co-authors include Gianluca Bontempi, Frédéric Lafitte, Kevin Kontos, Colas Schretter, Catharina Olsen, Daniel Marbach and Sushmita Mimi Roy. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, BMC Bioinformatics, Lecture notes in computer science, ORBi (University of Liège) and Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles).
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.