Rebecka J. Jornsten, Ph.D.
Affiliations: | 2001 | University of California, Berkeley, Berkeley, CA, United States |
Area:
Signal Processing (SP), Machine learning, Remote Sensing, NeuroscienceGoogle:
"Rebecka Jornsten"Parents
Sign in to add mentor| Bin Yu | grad student | 2001 | UC Berkeley | |
| (Data compression and its statistical implications, with an application to the analysis of microarray images.) | ||||
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Publications
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| Almstedt E, Elgendy R, Hekmati N, et al. (2020) Integrative discovery of treatments for high-risk neuroblastoma. Nature Communications. 11: 71 |
| Magnusson R, Mariotti GP, Köpsén M, et al. (2017) LASSIM-A network inference toolbox for genome-wide mechanistic modeling. Plos Computational Biology. 13: e1005608 |
| Kling T, Ferrarese R, Ó hAilín D, et al. (2016) Integrative Modeling Reveals Annexin A2-mediated Epigenetic Control of Mesenchymal Glioblastoma. Ebiomedicine |
| Kling T, Johansson P, Sanchez J, et al. (2015) Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content. Nucleic Acids Research |
| Kling T, Johansson P, Sanchez J, et al. (2015) Efficient exploration of multi-cancer networks by generalized covariance selection and interactive web content Cancer Research. 75: 2 |
| Gerlee P, Schmidt L, Monsefi N, et al. (2013) Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening Plos One. 8 |
| Jauhiainen A, Nerman O, Michailidis G, et al. (2012) Transcriptional and metabolic data integration and modeling for identification of active pathways. Biostatistics (Oxford, England). 13: 748-61 |
| Abenius T, Jörnsten R, Kling T, et al. (2012) System-scale network modeling of cancer using EPoC. Advances in Experimental Medicine and Biology. 736: 617-643 |
| Jörnsten R, Abenius T, Kling T, et al. (2011) Network modeling of the transcriptional effects of copy number aberrations in glioblastoma. Molecular Systems Biology. 7: 486 |
| Jörnsten R. (2009) Simultaneous Model Selection via Rate-Distortion Theory, With Applications to Cluster and Significance Analysis of Gene Expression Data Journal of Computational and Graphical Statistics. 18: 613-639 |