The Netherlands X-omics Initiative will have a strong focus on training and outreach. To support all researchers interested in X-omics, we will set up several training schools to educate about omics. These trainings and other suggested events will show in the event calendar. Our event calendar will have a strong focus on X-omics events in Europe. Supported by events related to one of the pillars in the Netherlands. The X-omics community will make it possible to communicate with other users of the X-omics infrastructure.
We will develop a portfolio of user trainings, in particular to educate new omics users in experimental design, sampling and data integration and interpretation. At the same time we will develop and provide trainings for omics practitioners including young talent and technicians at the different sites on understanding better the other omics techniques, on the implementation of (quality) protocols and FAIR data standards and on biostatistics, data integration, and modelling.
The X-omics consortium will organise different type of meetings in the coming 5 years. All meetings will be listed here. At least once a year a symposium will be organised to present the latest developments in the area of X-omics. You can register here:
Will be added soon
The X-omics infrastructure will be accessible to all researchers. To allow communication between the users of the infrastructure a X-omics community will be established.
This community will interact via:
● Social media
The publications of the X-omics consortium will be listed here!
Van Damme, T. et al. (2017). Mutations in ATP6V1E1 or ATP6V1A …. Am. J. Hum. Genet. 100, 216–227.
van Gool, A. J. et al. (2017). Bridging the translational innovation gap …. Nat. Rev. Drug Discov.
Snijder, J. et al. (2017). Structures of the cyanobacterial circadian oscillator …. Science 355, 1181–1184.
Blokzijl, F. et al. (2016). Tissue-specific mutation accumulation in human …. Nature 538, 260–264.
Jansen, E. J. R. et al. (2016). ATP6AP1 deficiency causes an immunodeficiency …. Nat. Commun. 7, 11600.
Liepe, J. et al. (2016). A large fraction of HLA class I ligands are …. Science 354, 354–358.
Tarailo-Graovac, M. et al. (2016). Exome Sequencing and the … .N. Engl. J. Med. 374, 2246–2255.
van Karnebeek, C. D. M. et al. (2016). NANS-mediated synthesis of sialic acid …. Nat. Genet. 48, 777–784.
Huch, M. et al. (2015). Long-term culture of genome-stable bipotent stem cells…. Cell 160, 299–312.
Liu, F., Rijkers, et. al. (2015). Proteome-wide profiling of protein a…. Nat. Methods 12, 1179–84.
Dane, A. D. et al. (2014). Integrating metabolomics profiling …. Anal. Chem. 86, 4110–4.
Hussein, S. M. I. et al. (2014). Genome-wide characterization of…. Nature 516, 198–206.
Tegtmeyer, L. C. et al. (2014). Multiple Phenotypes in … N. Engl. J. Med. 370, 533–542.
van Heesch, S. et al. (2014). Genomic and functional overlap between somatic and …. Cell Rep. 9, 2001–10.
Altelaar, A. F. M., et. al. (2013). Next-generation proteomics: …. Nat. Rev. Genet. 14, 35–48.
Gonzalez-Covarrubias, V. et al. (2013). Lipidomics of familial longevity. Aging Cell 12, 426–34.
Kettleborough, R. N. W. et al. (2013). A systematic genome-wide analysis of…. Nature 496, 494–7.
Low, T. Y. et al. (2013). Quantitative and qualitative proteome characteristics. Cell Rep. 5, 1469–78.
Peironcely, J. E. et al. (2013). Automated pipeline for de novo …. Anal. Chem. 85, 3576–83.
Raterink, R.-J et. al. (2013). T. Three-phase electroextraction: …. Anal. Chem. 85, 7762–8.
van der Kloet, F. M. et al. (2012). Discovery of early-stage biomarkers …Metabolomics 8, 109–119.
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