Research output per year
Research output per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Reader in Biostatistics and Computational Biology, Imperial College London
Aug 2014 → Oct 2017
W2 Professor (Senior Lecturer) in Medical Statistics and Bioinformatics, Universitat Leipzig
Feb 2007 → Aug 2014
Emmy Noether Group Leader (Lecturer), Dept. of Statistics, University of Munich
Jan 2002 → Jan 2007
Research Beacons, Institutes and Platforms
- Digital Futures
Fingerprint
Dive into the research topics where Korbinian Strimmer is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Quantification of protein abundance and interaction defines a mechanism for operation of the circadian clock
Koch, A., Bagnall, J., Smyllie, N. J., Begley, N., Adamson, A., Fribourgh, J. L., Spiller, D., Meng, Q.-J., Partch, C. L., Strimmer, K., House, T., Hastings, M. H. & Loudon, A., 14 Mar 2022, In: eLife. 11, e73976.Research output: Contribution to journal › Article › peer-review
Open Access -
A whitening approach to probabilistic canonical correlation analysis for omics data integration
Jendoubi, T. & Strimmer, K., 9 Jan 2019, In: BMC Bioinformatics. 20, 1, 15.Research output: Contribution to journal › Article › peer-review
Open Access -
Optimal Whitening and Decorrelation
Kessy, A., Lewin, A. & Strimmer, K., 2 Oct 2018, In: The American Statistician. 72, 4, p. 309-314 6 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Mass spectrometry analysis using MALDIquant
Gibb, S. & Strimmer, K., 2016, Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry. Datta, S. & Mertens, B. J. A. (eds.). Cham: Springer Nature, p. 101-124 (Frontiers in Probability and the Statistical Sciences).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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A simple data-adaptive probabilistic variant calling model
Hoffmann, S., Stadler, P. F. & Strimmer, K., 4 Mar 2015, In: Algorithms for Molecular Biology . 10Research output: Contribution to journal › Article › peer-review
Open Access
Projects
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SAU: Statistical Advisory Unit
Boshnakov, G. (PI), Charalambous, C. (PI), Foster, P. (PI), Hall, I. (PI), Han, Y. (PI), House, T. (PI), Johnson, O. (PI), Nadarajah, S. (PI), Papamarkou, T. (PI), Strimmer, K. (PI), Waite, T. (PI), Yuan, J. (PI) & Bhattacharjee, M. (PI)
Project: Research
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Prizes
Datasets
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Optimal Whitening and Decorrelation
Kessy, A. (Creator), Lewin, A. (Creator) & Strimmer, K. (Creator), figshare , 19 Jan 2017
DOI: 10.6084/m9.figshare.4568002
Dataset