Publications

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Publications

  1. van Rijswijk, M., Beirnaert, C., Caron, C. et al.The future of metabolomics in ELIXIR [version 1; referees: awaiting peer review]. F1000Research 2017, 6(ELIXIR):1649. DOI: 10.12688/f1000research.12342.1
  2. Meier, R., Ruttkies, C., Treutler,H. , and Neumann, S. Bioinformatics can boost metabolomics research. J Biotechnol. 2017 May 26. pii: S0168-1656(17)30253-5. DOI:10.1016/j.jbiotec.2017.05.018
  3. Herman, S., Emami Khoonsari, P., Aftab, O., Krishnan, S., Strömbom, E., Larsson, R., Hammerling, U., Spjuth, O., Kultima, K., and Gustafsson, M. Mass spectrometry based metabolomics for in vitro systems pharmacology: pitfalls, challenges, and computational solutionsMetabolomics. 2017;13(7):79. DOI:10.1007/s11306-017-1213-z
  4. Cacciatore, S., Tenori, L., Luchinat, C., Bennett, P.R and MacIntyre, D.A. KODAMA: an R package for knowledge discovery and data miningBioinformatics. 2017 15;33(4):621-623. DOI:10.1093/bioinformatics/btw705
  5. Takis, P.G., Tenori, L., Ravera, E. and Luchinat, C. Gelified Biofluids for High-Resolution Magic Angle Spinning 1H NMR Analysis: The Case of Urine. Anal Chem. 2017 89(2):1054-1058.DOI:10.1021/acs.analchem.6b04318
  6. Haug, K, Salek, R.M. and Steinbeck, C. Global open data management in metabolomicsCurr Opin Chem Biol.2017. DOI: 10.1016/j.cbpa.2016.12.024
  7. Selivanov, V.A., Benito, A., Miranda, A., Aguilar, E., Polat I.H., Centelles, J.J., Jayaraman, A., Lee, P.W., Marin, S. and Cascante, M. MIDcor, an R-program for deciphering mass interferences in mass spectra of metabolites enriched in stable isotopes. BMC Bioinformatics. 2017. DOI: 10.1186/s12859-017-1513-3
  8. Bandrowski, A., Brinkman, R., Brochhausen, M., Brush, M.H, Bug, B., Chibucos, M.C., Clancy, K. et al. The Ontology for Biomedical Investigations. PLoS One. 2016 Apr 29;11(4):e0154556. DOI:10.1371/journal.pone.0154556
  9. Karaman, I., Ferreira, D.L., Boulange, C.L., Kaluarachchi, M.R., Herrington, D., Dona, A.C, Castagné, R. et al. (2016) A Workflow For Integrated Processing of Multi-Cohort Untargeted 1H NMR Metabolomics Data In Large ScaleMetabolic EpidemiologyJ Proteome Res. 2016 Sep 15. DOI: 10.1021/acs.jproteome.6b00125
  10. Saccenti, E., Menichetti, G., Ghini, V., Remondini, D., Tenori, L., and Luchinat, C. (2016) EntropyBased Network Representation of the Individual Metabolic PhenotypeJ Proteome Res. Sep 2; 15(9): 3298-307. DOI:10.1021/acs.jproteome.6b00454
  11. Blaise, B.J., Correia, G., Tin, A., Young, J.H., Vergnaud, A.C., Lewis, M., Pearce, J.T.  et al. (2016) Power Analysis and Sample Size Determination in Metabolic Phenotyping. Anal Chem. May 17; 88(10): 5179-88. DOI:10.1021/acs.analchem.6b00188
  12. Merlet, B., Paulhe N., Vinson, F., Frainay, C., Chazalvie,l M., Poupin, N., Gloaguen, Y. et al. (2016) A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale MetabolicNetworksFront Mol Biosci., Feb 16; 3:2. DOI:  10.3389/fmolb.2016.00002
  13. Rocca-Serra, P., Salek, R.M., Arita, M., Correa, E., Dayalan, S., Gonzalez-Beltran A., Ebbels T. et al. (2016) Data standards can boost metabolomics research, and if there is a will, there is a way. Metabolomics, 12(1):14. DOI: 10.1007/s11306-015-0879-3

Newsletter, Articles and News

  1. Philippe Rocca-Sera. PhenoMeNal: Virtual e-Infrastructure supporting Clinical Research and Metabolism Studies. OeRC News. (November 2016)
  2. SNIC Science Cloud – Virtual Research Environments for Clinical Metabolomics (April 2016)
  3. Namrata Kale, Christoph Steinbeck and PhenoMeNal Consortium. PhenoMeNal—An e-infrastructure for analysis of metabolic phenotype data. Metabolomics Spotlight, MetaboNews (January, 2016).
  4. Toxalim – The European project PhenoMeNal (Horizon 2020) launched on September 1st, 2015
  5. Life Science Sweden (Swedish Newspaper) – Tar fram infrastruktur för metabolomik (September 2015)
  6. SciLifeLab – PhenoMeNal: a gateway to personalised medicine (September 2015)
  7. Uppsala Universitet – PhenoMeNal: The gateway to individually adapted medication (September 2015)
  8. DTL – PhenoMeNal project to build an e-infrastructure for clinical metabolomics data (September 2015)
  9. EMBL-EBI Press release – Phenomenal: a gateway to personalised medicine (September 2015)
  10. Namrata Kale and Christoph Steinbeck. PhenoMeNal: towards an e-Infrastructure for pheno- and genotyping data. EGI (2015).