الانتماءات

• العلوم البيولوجية
• علوم الحاسب الآلي

المؤهل العلمي

الاهتمامات البحثية

مؤلفات مختارة

• Zenil, Kiani and Tegner. Algorithmic Information Dynamics, Monograph, Cambridge University Press, 2019
• Zenil, Kiani and Tegner. Algorithmic Cognition, Monograph, Springer, 2019
• Zenil, Kiani and Tegner. Graph and Tensor Complexity, Monograph, Springer, 2019
• Zenil et al. A review of graph and network complexity from an algorithmic information perspective, 20, (551), Entropy, 2018
• Kular et al. DNA methylation at HLA as a mediator of the DRB1*15:01 risk haplotype and a novel protective variant in Multiple Sclerosis Nature Communications, 2018
• Zenil et al. A decomposition method for global evaluation of Shannon entropy and local estimation of algorithmic complexity 20, (605) Entropy, 2018
• Kotelnikova et al. Dynamics and heterogeneity of brain damage in multiple sclerosis, PLoS computational biology 13 (10), e1005757, 2017
• H Zenil, NA Kiani, J Tegnér, Low-algorithmic-complexity entropy-deceiving graphs, Physical Review E 96 (1), 012308, 2017
• Gomez-Cabrero, et al. On the emergence of short advanced courses in Systems Medicine and Biology: recent experiences and recommended guidelines. Cell Systems September, 2017
• David Gomez-Cabrero, and Jesper Tegnér.  Iterative Systems Biology for Medicine – time for advancing from networks signature to mechanistic equations Current Opinion in Systems Biology May, 2017
• Manuel Zeitelhofera, et al. Functional genomics analysis of vitamin D effects on CD4+ T-cells in vivo in experimental autoimmune encephalomyelitis PNAS February, 2017
• Hill, S. et al. Empirical assessment of causal network learning through a community-based effort Nature Methods, 2016.
• Rodríguez-Cortez, et al. Monozygotic twins discordant for common variable immunodeficiency reveal impaired DNA demethylation during naïve-to-memory B-cell transition Nature Communications 6/17, 2015.
• Yang, et al. VEGF-B promotes cancer metastasis through a VEGF-A–independent mechanism and serves as a marker of poor prognosis for cancer patients PNAS 5/19, 2015.
• Lindholm, et al. An integrative analysis reveals coordinated reprogramming of the epigenome in human skeletal muscle after training Epigenetics.12/2, 1557-69. 2014
• Gomez-Cabrero et al. Data integration in the era of omics: current and future challenges. BMC Systems Biology, vol 8 (Supp 2):I1),2014
• Marabita, et al. An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform Volume 8, Issue 3 Epigenetics March, 8(3), 333–46., 2013
• Teschendorff et al. S A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinum 450k DNA methylation data Bioinformatics. Jan 15;29(2):189-96, 2013
• Ravasi et al. An atlas of combinatorial transcriptional regulation in mouse and man, Cell. Mar 5;140(5):744-52. 2010
• Suzuki et al. A complex transcriptional network controls growth arrest and differentiation in a human myeloid leukemia cell line, Nature Genetics May;41(5):553-62. Epub 2009 Apr 19, 2009
• Pena, J., Nilsson, R, Björkegren, J. and Tegnér, J. An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity. Journal of Machine Learning Research 2009.
• Fredrik Edin, et al. Mechanism for Top-down Control of Working Memory Capacity. PNAS Apr 21;106(16):6802-7. Epub Apr 1.2009
• Peña, J. M., Nilsson, R., Björkegren, J. and Tegnér, J. Towards scalable and Data Efficient Learning of Markov Boundaries,International Journal of Approximate Reasoning, Volume 45, Issue 2, Pages 211-232 2007
• Tegnér, J. and Björkegren, J. Perturbations to uncover gene networks. Trends in Genetics, Jan;23(1):34-41, 2007
• Nilsson, R., Peña, J. M., Björkegren J., and J. Tegnér, Consistent feature selection for pattern recognition in polynomial time,Journal of Machine Learning Research, 8(March):589-612, 2007
• Carninci, T. et al. The transcriptional landscape of the mammalian genome, Science. Sep 2;309 (5740):1559-63. 2005
• Tegnér, J., et al. Reverse engineering gene networks -- integrating genetic perturbations with dynamical modeling. PNAS. 100,5944-5949, 2003.