Journal article

Gene network inference and visualization tools for biologists: application to new human transcriptome datasets

Daniel Hurley, Hiromitsu Araki, Yoshinori Tamada, Ben Dunmore, Deborah Sanders, Sally Humphreys, Muna Affara, Seiya Imoto, Kaori Yasuda, Yuki Tomiyasu, Kosuke Tashiro, Christopher Savoie, Vicky Cho, Stephen Smith, Satoru Kuhara, Satoru Miyano, D Stephen Charnock-Jones, Edmund J Crampin, Cristin G Print

Nucleic Acids Research | OXFORD UNIV PRESS | Published : 2012

University of Melbourne Researchers

Grants

Awarded by Royal Society of New Zealand


Awarded by University of Auckland


Awarded by Health Research Council of New Zealand


Awarded by University of Auckland Faculty of Medical and Health Sciences


Awarded by Grants-in-Aid for Scientific Research


Funding Acknowledgements

Research collaboration agreements between the University of Cambridge and GNI Ltd for generation of the endothelial cell data used in this work, and the implementation of Bayesian gene network inference methods; the University of Auckland Doctoral Scholarship (to D. H.); Maurice Wilkins Centre for Molecular Biodiscovery Studentship (to D. H.); Auckland Bioengineering Institute (to D. H.); Marsden Fund of the Royal Society of New Zealand (06-UOA-182 to E.J.C.); University of Auckland Early Career Research Excellence Award (#3606318 to E.J.C.); Health Research Council of New Zealand International Investment Opportunities Fund (06/581 to C. P.); University of Auckland Faculty of Medical and Health Sciences Research Development Fund (# 8303460 to C. P.); University of Auckland Vice-Chancellor's Development Fund (# 23285 to C. P.); Maurice Wilkins Centre of Research Excellence Fund. Funding for open access charge: Departmental Grant funding.