Silke Janitza
Impact in
- Ecological Modeling top 10%
- Species Distribution and Climate Change
- Statistics and Probability top 5%
- Statistical Methods and Inference
Papers in
-
- Statistical Methods and Inference 10
- Advanced Statistical Methods and Models 3
- Statistical Methods and Bayesian Inference 2
- Co-authors
- Anne‐Laure BoulesteixJochen KruppaInke R. KönigRoman HornungCarolin StroblGerhard TutzRiccardo De BinWilli Sauerbrei
- Journals
- Biometrical Journal (3 papers)Advances in Data Analysis and Classification (2 papers)PLoS ONE (2 papers)Journal of Clinical Monitoring and Computing (1 paper)The Annals of Thoracic Surgery (1 paper)
- Partner nations
- GermanyNetherlandsSwitzerland
In The Last Decade
Silke Janitza
24 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 204
- Ecological Modeling 53
- Statistics and Probability 97
- Health Information Management 45
- Environmental Engineering 125
- Global and Planetary Change 162
Countries citing papers authored by Silke Janitza
This map shows the geographic impact of Silke Janitza'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 Silke Janitza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silke Janitza more than expected).
Fields of papers citing papers by Silke Janitza
This network shows the impact of papers produced by Silke Janitza. 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 Silke Janitza. The network helps show where Silke Janitza may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Silke Janitza, 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 | 2019 | 29 | |
| 2 | 2018 | 173 | |
| 3 | 2018 | 12 | |
| 4 | 2018 | 59 | |
| 5 | 2018 | 13 | |
| 6 | 2018 | 2 | |
| 7 | 2017 | 28 | |
| 8 | 2017 | 10 | |
| 9 | 2016 | 5 | |
| 10 | 2016 | 17 | |
| 11 | 2016 | 56 | |
| 12 | 2016 | 11 | |
| 13 | 2016 | 127 | |
| 14 | 2016 | 17 | |
| 15 | 2015 | 68 | |
| 16 | 2015 | 2 | |
| 17 | 2014 | 1 | |
| 18 | 2014 | 19 | |
| 19 | 2013 | 9 | |
| 20 | 2013 | 193 |
About Silke Janitza
Silke Janitza is a scholar working on Statistics and Probability, Geriatrics and Gerontology, Ecological Modeling, Artificial Intelligence and Anesthesiology and Pain Medicine, having authored 24 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (10 papers), Gene expression and cancer classification (4 papers), Advanced Statistical Methods and Models (3 papers), Data Mining Algorithms and Applications (3 papers), Transplantation: Methods and Outcomes (3 papers), Statistical Methods and Bayesian Inference (2 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Ecological Modeling (53 citations), Statistics and Probability (97 citations), Health Information Management (45 citations), Environmental Engineering (125 citations) and Global and Planetary Change (162 citations). Silke Janitza has collaborated with scholars based in Germany, Netherlands and Switzerland. Frequent co-authors include Anne‐Laure Boulesteix, Jochen Kruppa, Inke R. König, Roman Hornung, Carolin Strobl, Gerhard Tutz, Riccardo De Bin, Willi Sauerbrei, Thomas Weig and Heike Hölling. Their work appears in journals such as Biometrical Journal, Advances in Data Analysis and Classification, PLoS ONE, Journal of Clinical Monitoring and Computing and The Annals of Thoracic Surgery.
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.