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author peterjc
date Fri, 25 Oct 2013 10:20:01 -0400
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50 ======== 50 ========
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52 If you use this workflow directly, or a derivative of it, in work leading 52 If you use this workflow directly, or a derivative of it, in work leading
53 to a scientific publication, please cite: 53 to a scientific publication, please cite:
54 54
55 Cock, P.J.A. and Pritchard, L. 2013. Galaxy as a platform for identifying 55 Cock, P.J.A. and Pritchard, L. (2014). Galaxy as a platform for identifying
56 candidate pathogen effectors. Chapter 1 in "Plant-Pathogen Interactions: 56 candidate pathogen effectors. Chapter 1 in "Plant-Pathogen Interactions:
57 Methods and Protocols (Second Edition)"; Methods in Molecular Biology. 57 Methods and Protocols (Second Edition)"; P. Birch, J. Jones, and J.I. Bos, eds.
58 Humana Press, Springer. In press. 58 Methods in Molecular Biology. Humana Press, Springer. ISBN 978-1-62703-985-7.
59 http://www.springer.com/life+sciences/plant+sciences/book/978-1-62703-985-7
59 60
60 For the associated RXLR Galaxy tool, please cite: 61 For the associated RXLR Galaxy tool, please cite:
61 62
62 Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013). 63 Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013).
63 Galaxy tools and workflows for sequence analysis with applications 64 Galaxy tools and workflows for sequence analysis with applications