-------- Original Message -------- Subject: Learning At gene functions - a challenge? Date: Wed, 24 Jun 2009 14:35:16 +0100 From: Andrew Millar <Andrew.Millar@ed.ac.uk> To: schoof@mpiz-koeln.mpg.de <schoof@mpiz-koeln.mpg.de>, rodrigo.gutierrez@gmail.com <rodrigo.gutierrez@gmail.com> CC: cdtown@jcvi.org <cdtown@jcvi.org>, flegeai@infobiogen.fr <flegeai@infobiogen.fr>, yvdp@psb.UGent.be <yvdp@psb.UGent.be>, yn@kazusa.or.jp <yn@kazusa.or.jp>, philip.benfey@duke.edu <philip.benfey@duke.edu>, mash@iastate.edu <mash@iastate.edu>, Wilhelm Gruissem <wgruissem@ethz.ch> Dear MASC BI and SysBio members, I have just met Quaid Morris, machine learning PI from U Toronto. Nick Provart has clearly done a great job of selling Arabidopsis to him. Quaid talked about the 'MouseFunc challenge' for assigning gene functions based on machine learning from genomic data sets. With a broad-scale At interactome coming up soon, I asked if this was somethign the A.t. community could consider, and he reacted very positively. I know that at least some of Olga Tronskaya's lab are also interested in plants, and Insuk Lee from Ed Marcotte's lab has been developing his FunctionalNet for Arabidopsis. Hence there is enough interest from that community. Apologies in advance if this is something you have already considered. If not, maybe we could discuss at the upcoming meeting? http://hugheslab.med.utoronto.ca/supplementary-data/mouseFunc_I/ has the details. The key ingredients were: - a 'host' lab to establish the challenge; a potential conflict was that the host also participated as a contestant - we might avoid that. - Genome Biology journal was lined up to publish a paper on the challenge and papers on the best results - they had a professional annotator to look at the consensus of the best networks and comment on it. We might get the consensus published as well as the individual efforts. Also, theirs was by invitation only, we could be more open and international. Best regards, Andrew -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. -- Yves Van de Peer, PhD. Professor in Bioinformatics and Genome Biology Group Leader Bioinformatics and Evolutionary Genomics VIB Department of Plant Systems Biology, UGent Ghent University Technologiepark 927 B-9052 Ghent Belgium Phone: +32 (0)9 331 3807 Cell Phone: +32 (0)476 560 091 Fax: +32 (0)9 331 3809 email: yves.vandepeer@psb.vib-ugent.be http://bioinformatics.psb.ugent.be/