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Nat Biotechnol. 2015 Feb;33(2):137-9. doi: 10.1038/nbt.3134.

Multi-omic data analysis using Galaxy.

Author information

1
1] Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden. [2] Bioinformatics Infrastructure for Life Sciences (BILS), Stockholm, Sweden.
2
1] Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, USA. [2] Department of Biochemistry and Molecular Biology, Pennsylvania State University, State College, Pennsylvania, USA.
3
1] Department of Biochemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia. [2] Life Sciences Computation Centre, Victorian Life Sciences Computation Initiative, Melbourne, Australia.
4
Analytical Biochemistry, Department of Pharmacy, University of Groningen, Groningen, The Netherlands.
5
1] Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, USA. [2] Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, USA.
6
School of Biotechnology, Science for Life Laboratory, Royal Institute of Technology - KTH, Stockholm, Sweden.
7
Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.
8
Plant Research International, Wageningen University and Research Center, Wageningen, The Netherlands.
9
Bioinformatics Laboratory, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
10
Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, USA.
PMID:
25658277
DOI:
10.1038/nbt.3134
[Indexed for MEDLINE]

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