Barbara Rakitsch
Impact in
- Genetics top 10%
- Genetic Mapping and Diversity in Plants and Animals
- Genetic and phenotypic traits in livestock
- Genetic Associations and Epidemiology
Papers in
-
- Bioinformatics and Genomic Networks 2
- Gene expression and cancer classification 2
-
- Gaussian Processes and Bayesian Inference 3
- Neural Networks and Applications 2
- Co-authors
- Oliver Stegle (5 shared papers)Karsten Borgwardt (5 shared papers)Christoph Lippert (3 shared papers)Francesco Paolo Casale (2 shared papers)Limin Li (1 shared paper)Dominik G. Grimm (2 shared papers)Daniel Koenig (1 shared paper)Anette Habring‐Müller (1 shared paper)
- Journals
- Bioinformatics (2 papers)Nature Methods (1 paper)PLoS Genetics (1 paper)Molecular Biology and Evolution (1 paper)Genome biology (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Barbara Rakitsch
14 papers receiving 334 citations
Peers
Comparison fields: 5 of 73
- Aging 13
- Genetics 202
- Plant Science 87
- Molecular Biology 130
- Statistics and Probability 10
Countries citing papers authored by Barbara Rakitsch
This map shows the geographic impact of Barbara Rakitsch'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 Barbara Rakitsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barbara Rakitsch more than expected).
Fields of papers citing papers by Barbara Rakitsch
This network shows the impact of papers produced by Barbara Rakitsch. 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 Barbara Rakitsch. The network helps show where Barbara Rakitsch may publish in the future.
Co-authors
The 25 scholars most cited alongside Barbara Rakitsch, 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 | 2012 | 87 | |
| 2 | 2015 | 59 | |
| 3 | 2016 | 48 | |
| 4 | It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals | 2013 | 29 |
| 5 | 2016 | 28 | |
| 6 | 2018 | 24 | |
| 7 | 2011 | 23 | |
| 8 | 2016 | 15 | |
| 9 | 2017 | 13 | |
| 10 | 2024 | 7 | |
| 11 | 2018 | 3 | |
| 12 | 2023 | 2 | |
| 13 | Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes | 2020 | 1 |
| 14 | 2022 | 1 |
About Barbara Rakitsch
Barbara Rakitsch is a scholar working on Molecular Biology, Artificial Intelligence, Genetics, Control and Systems Engineering and Statistical and Nonlinear Physics, having authored 14 papers that have together received 340 indexed citations. Recurring topics across this work include Genetic Mapping and Diversity in Plants and Animals (4 papers), Genetic Associations and Epidemiology (3 papers), Genetic and phenotypic traits in livestock (3 papers), Gaussian Processes and Bayesian Inference (3 papers), Neural Networks and Applications (2 papers), Bioinformatics and Genomic Networks (2 papers), Model Reduction and Neural Networks (2 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Aging (13 citations), Genetics (202 citations), Plant Science (87 citations), Molecular Biology (130 citations) and Statistics and Probability (10 citations). Barbara Rakitsch has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Oliver Stegle, Karsten Borgwardt, Christoph Lippert, Francesco Paolo Casale, Limin Li, Dominik G. Grimm, Daniel Koenig, Anette Habring‐Müller, Carmen Martín‐Pizarro and François Vasseur. Their work appears in journals such as Bioinformatics, Nature Methods, PLoS Genetics, Molecular Biology and Evolution and Genome biology.
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.