Daniela Witten
Impact in
- Statistics and Probability top 0.2%
- Statistical Methods and Inference
- Genetics top 0.2%
- Genomics and Rare Diseases
- Genetic Associations and Epidemiology
Papers in
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- Statistical Methods and Inference 31
- Advanced Statistical Methods and Models 8
- Statistical Methods and Bayesian Inference 6
-
- Gene expression and cancer classification 24
- Bioinformatics and Genomic Networks 6
- Genomics and Chromatin Dynamics 5
- Co-authors
- Robert TibshiraniTrevor HastieGareth JamesJay ShendureGregory M. CooperMartin KircherBrian J. O’RoakPhilipp Rentzsch
- Journals
- Journal of the American Statistical Association (9 papers)Biometrika (6 papers)Journal of Computational and Graphical Statistics (5 papers)Biostatistics (5 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (4 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Daniela Witten
89 papers receiving 22.5k citations
Hit Papers
Peers
Comparison fields: 5 of 238
- Statistics and Probability 1.5k
- Genetics 3.8k
- Computational Mathematics 66
- Molecular Biology 6.9k
- Cancer Research 1.5k
Countries citing papers authored by Daniela Witten
This map shows the geographic impact of Daniela Witten'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 Daniela Witten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Witten more than expected).
Fields of papers citing papers by Daniela Witten
This network shows the impact of papers produced by Daniela Witten. 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 Daniela Witten. The network helps show where Daniela Witten may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniela Witten, 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 | 2025 | 0 | |
| 2 | An Introduction to Statistical Learning Hit paper breakdown → | 2023 | 369 |
| 3 | 2022 | 27 | |
| 4 | 2021 | 18 | |
| 5 | 2020 | 15 | |
| 6 | Distributionally Robust Reduced Rank Regression and Principal Component Analysis in High Dimensions. | 2018 | 2 |
| 7 | An Introduction to Statistical Learning: with Applications in R Hit paper breakdown → | 2018 | 1777 |
| 8 | 2017 | 8 | |
| 9 | 2016 | 179 | |
| 10 | 2014 | 32 | |
| 11 | 2013 | 38 | |
| 12 | 2012 | 29 | |
| 13 | 2012 | 81 | |
| 14 | 2012 | 235 | |
| 15 | 2011 | 239 | |
| 16 | 2010 | 136 | |
| 17 | A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis Hit paper breakdown → | 2009 | 954 |
| 18 | 2009 | 376 | |
| 19 | 2009 | 263 | |
| 20 | 2008 | 7 |
About Daniela Witten
Daniela Witten is a scholar working on Statistics and Probability, Molecular Biology, Artificial Intelligence, Cancer Research and Statistics, Probability and Uncertainty, having authored 91 papers that have together received 23.1k indexed citations. Recurring topics across this work include Statistical Methods and Inference (31 papers), Gene expression and cancer classification (24 papers), Advanced Statistical Methods and Models (8 papers), Bayesian Methods and Mixture Models (7 papers), Statistical Methods and Bayesian Inference (6 papers), Bioinformatics and Genomic Networks (6 papers), Genomics and Chromatin Dynamics (5 papers) and Bayesian Modeling and Causal Inference (5 papers). The work is most often cited by research in Statistics and Probability (1.5k citations), Genetics (3.8k citations), Computational Mathematics (66 citations), Molecular Biology (6.9k citations) and Cancer Research (1.5k citations). Daniela Witten has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Robert Tibshirani, Trevor Hastie, Gareth James, Jay Shendure, Gregory M. Cooper, Martin Kircher, Brian J. O’Roak, Philipp Rentzsch, Patrick Danaher and Pei Wang. Their work appears in journals such as Journal of the American Statistical Association, Biometrika, Journal of Computational and Graphical Statistics, Biostatistics and Journal of the Royal Statistical Society Series B (Statistical Methodology).
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.