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<span style="font-size:12pt">NIPS 2015 workshop on Machine Learning in Computational Biology</span><br>
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<font face="Calibri,Arial,Helvetica,sans-serif">Call for contributions</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> Workshop on Machine Learning in Computational Biology</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> http://www.mlcb.org</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> A workshop at the Twenty-Ninth Annual Conference on</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> Neural Information Processing Systems (NIPS 2015)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> Montreal, QC, Canada, December 12, 2015.</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Important dates:</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Oct 4, 2015 : Deadline for submission of extended abstracts</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Oct 22, 2015: Acceptance notification</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Dec 12, 2015: Workshop date</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">WORKSHOP DESCRIPTION</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> The field of computational biology has seen dramatic growth over the past few years. A wide range of high-throughput technologies developed in the last decade now enable us to measure parts of a biological
system at various resolutions—at the genome, epigenome, transcriptome, and proteome levels. These technologies are now being used to collect data for an ever-increasingly diverse set of problems, ranging from classical problems such as predicting differentially
regulated genes between time points and predicting subcellular localization of RNA and proteins, to models that explore complex mechanistic hypotheses bridging the gap between genetics and disease, population genetics and transcriptional regulation. Fully
realizing the scientific and clinical potential of these data requires developing novel supervised and unsupervised learning methods that are scalable, can accommodate heterogeneity, are robust to systematic noise and confounding factors, and provide mechanistic
insights. </font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif"> The goals of this workshop are to i) present emerging problems and innovative machine learning techniques in computational biology, and ii) generate discussion on how to best model the intricacies of biological
data and synthesize and interpret results in light of the current work in the field. We will invite several rising leaders from the biology/bioinformatics community who will present current research problems in computational biology and lead these discussions
based on their own research and experiences. We will also have the usual rigorous screening of contributed talks on novel learning approaches in computational biology. We encourage contributions describing either progress on new bioinformatics problems or
work on established problems using methods that are substantially different from established alternatives. Kernel methods, graphical models, feature selection, non-parametric models and other techniques applied to relevant bioinformatics problems would all
be appropriate for the workshop. We are particularly keen on considering contributions related to the prediction of functions from genotypes and that target data generated from novel technologies such as gene editing and single cell genomics, though we will
consider all submissions that highlight applications of machine learning into computational biology. The targeted audience are people with interest in learning and applications to relevant problems from the life sciences, including NIPS participants without
any existing research link to computational biology.</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">SUBMISSION INSTRUCTIONS</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Researchers interested in contributing should upload an extended</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">abstract of 4 pages in PDF format to the MLCB submission web site</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">https://easychair.org/conferences/?conf=mlcb2015</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">by Oct 4, 2015, 11:59pm (time zone of your choice).</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">No special style is required. Authors may use the NIPS style file, but</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">are also free to use other styles as long as they use standard font </font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">size (11 pt) and margins (1 in). </font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">*Submissions should be suitably anonymized and meet the</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">requirements for double-blind reviewing.*</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">All submissions will be anonymously peer reviewed and will be</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">evaluated on the basis of their technical content. A strong</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">submission to the workshop typically presents a new learning method</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">that yields new biological insights, or applies an existing learning</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">method to a new biological problem. However, submissions that improve</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">upon existing methods for solving previously studied problems will</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">also be considered. Examples of research presented in previous years</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">can be found online at http://www.mlcb.org/nipscompbio/previous/.</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">The workshop allows submissions of papers that are under review or</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">have been recently published in a conference or a journal. This is</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">done to encourage presentation of mature research projects that are</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">interesting to the community. The authors should clearly state any</font></div>
<div style="font-family:Calibri,Arial,Helvetica,sans-serif; margin-top:0px; margin-bottom:0px">
<font face="Calibri,Arial,Helvetica,sans-serif">overlapping published work at time of submission. </font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Send any questions to mlcb2015@easychair.org.</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">INVITED SPEAKERS</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Dana Pe’er (Associate Professor of Biology and Systems Biology, Columbia University)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Matthew Stephens (Professor of Statistics and Human Genetics, University of Chicago)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">ORGANIZERS</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Nicolo Fusi (Microsoft Research)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Anna Goldenberg (University of Toronto)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Sara Mostafavi (UBC)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Gerald Quon (UC Davis)</font></div>
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<font face="Calibri,Arial,Helvetica,sans-serif">Oliver Stegle (EMBL-EBI)</font></div>
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