Ernst C. Wit
Impact in
- Aging top 2%
- Statistics and Probability top 1%
- Statistical Methods and Inference
Papers in
-
- Gene Regulatory Network Analysis 28
- Gene expression and cancer classification 21
- Bioinformatics and Genomic Networks 16
-
- Statistical Methods and Inference 15
- Statistical Methods and Bayesian Inference 9
- Co-authors
- John McClure (4 shared papers)Raya Khanin (8 shared papers)Edwin R. van den Heuvel (6 shared papers)Jan‐Willem Romeijn (1 shared paper)Matthias Heinemann (4 shared papers)Fentaw Abegaz (7 shared papers)Shane M. Meehan (2 shared papers)Mark Haas (2 shared papers)
- Journals
- Bioinformatics (6 papers)Journal of the Royal Statistical Society Series C (Applied Statistics) (6 papers)Statistics and Computing (5 papers)BMC Bioinformatics (5 papers)Biostatistics (4 papers)
- Partner nations
- NetherlandsSwitzerlandUnited Kingdom
In The Last Decade
Ernst C. Wit
131 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 190
- Aging 100
- Statistics and Probability 272
- Biophysics 112
- Molecular Biology 978
- Nephrology 93
Countries citing papers authored by Ernst C. Wit
This map shows the geographic impact of Ernst C. Wit'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 Ernst C. Wit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ernst C. Wit more than expected).
Fields of papers citing papers by Ernst C. Wit
This network shows the impact of papers produced by Ernst C. Wit. 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 Ernst C. Wit. The network helps show where Ernst C. Wit may publish in the future.
Co-authors
The 25 scholars most cited alongside Ernst C. Wit, 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 136 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 225 | |
| 2 | 2012 | 217 | |
| 3 | 2000 | 173 | |
| 4 | 2006 | 160 | |
| 5 | 2015 | 133 | |
| 6 | Statistics for Microarrays : Design, Analysis and Inference | 2004 | 127 |
| 7 | 2004 | 118 | |
| 8 | 2007 | 111 | |
| 9 | 2016 | 103 | |
| 10 | 2003 | 82 | |
| 11 | 2004 | 76 | |
| 12 | 2013 | 65 | |
| 13 | 2009 | 56 | |
| 14 | 2017 | 51 | |
| 15 | 2017 | 49 | |
| 16 | Identification from public data of molecular markers of adenocarcinoma characteristic of the site of origin. | 2002 | 49 |
| 17 | 2019 | 49 | |
| 18 | 2005 | 46 | |
| 19 | 2014 | 38 | |
| 20 | 2009 | 38 |
About Ernst C. Wit
Ernst C. Wit is a scholar working on Molecular Biology, Statistics and Probability, Artificial Intelligence, Statistical and Nonlinear Physics and Genetics, having authored 136 papers that have together received 2.8k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (28 papers), Gene expression and cancer classification (21 papers), Bioinformatics and Genomic Networks (16 papers), Statistical Methods and Inference (15 papers), Complex Network Analysis Techniques (12 papers), Mental Health Research Topics (10 papers), Bayesian Methods and Mixture Models (10 papers) and Statistical Methods and Bayesian Inference (9 papers). The work is most often cited by research in Aging (100 citations), Statistics and Probability (272 citations), Biophysics (112 citations), Molecular Biology (978 citations) and Nephrology (93 citations). Ernst C. Wit has collaborated with scholars based in Netherlands, Switzerland and United Kingdom. Frequent co-authors include John McClure, Raya Khanin, Edwin R. van den Heuvel, Jan‐Willem Romeijn, Matthias Heinemann, Fentaw Abegaz, Shane M. Meehan, Mark Haas, Benjamin H. Spargo and Veronica Vinciotti. Their work appears in journals such as Bioinformatics, Journal of the Royal Statistical Society Series C (Applied Statistics), Statistics and Computing, BMC Bioinformatics and Biostatistics.
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.