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NIPS 2013 workshop on Machine Learning in Computational Biology
United States - NV - Lake Tahoe

Hosted by: NIPS
Dates: Dec 09, 2013 through Dec 10, 2013

Call for Proceedings Presentations: 2013-09-04 through 2013-10-22
 
Description
 
NIPS 2013 workshop on Machine Learning in Computational Biology
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Call for contributions

Workshop on Machine Learning in Computational Biology

http://www.mlcb.org


A workshop at the Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013)
Lake Tahoe, Nevada, USA, December 9 or 10, 2013.

Important dates:
Oct 22, 2013 : Deadline for submission of extended abstracts
Nov 4, 2013: Acceptance notification
Dec 9 or 10, 2013: Workshop date

WORKSHOP DESCRIPTION

The field of computational biology has seen dramatic growth over the past few years, in terms of newly available data, new scientific questions and new challenges for learning and inference. In particular, biological data is often relationally structured and highly diverse, and thus requires combining multiple weak evidence from heterogeneous sources. These sources include sequenced genomes of a variety of organisms, gene expression data from multiple technologies, protein sequence and 3D structural data, protein interaction data, gene ontology and pathway databases, genetic variation data (such as SNPs), high-content phenotypic screening data, and an enormous amount of text data in the biological and medical literature. New
types of scientific and clinical problems require novel supervised and unsupervised learning approaches that can use these growing resources. Furthermore, next generation sequencing technologies are yielding terabyte scale data sets that require novel algorithmic solutions.

The workshop will host presentations of emerging problems and machine learning techniques 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 standard approaches. Kernel methods, graphical models, semi-supervised approaches, feature selection and other techniques applied to relevant bioinformatics problems would all be appropriate for the workshop.

SUBMISSION INSTRUCTIONS

Researchers interested in contributing should upload an extended abstract of 4 pages in PDF format to the MLCB submission web site http://www.easychair.org/conferences/?conf=mlcb2013 by Oct 22, 2013, 11:59pm (time zone of your choice).

No special style is required. Authors may use the NIPS style file, but are also free to use other styles as long as they use standard font size (11 pt) and margins (1 in).

*Submissions should be suitably anonymized and meet the requirements for double-blind reviewing.*

All submissions will be anonymously peer reviewed and will be evaluated on the basis of their technical content. A strong submission to the workshop typically presents a new learning method that yields new biological insights, or applies an existing learning method to a new biological problem. However, submissions that improve upon existing methods for solving previously studied problems will also be considered. Examples of research presented in previous years can be found online at http://www.mlcb.org/nipscompbio/previous/.

The workshop allows submissions of papers that are under review or have been recently published in a conference or a journal. This is done to encourage presentation of mature research projects that are interesting to the community. The authors should clearly state any overlapping published work at time of submission.

INVITED SPEAKERS

Jonathan Pritchard (Stanford)
Samuel Kaski (HIIT)

ORGANIZERS

Anna Goldenberg (University of Toronto)
Sara Mostafavi (Stanford)
Oliver Stegle (EMBL)
Jean-Philippe Vert (Mines ParisTech, Institut Curie)
 
Additional Information
 
Event URL: http://www.mlcb.org
ISCB Member Discount: None

While ISCB provides for conference and event listings that may be of interest to members and bioinformaticians at large, ISCB is not responsible for the content provided by outside sources. Such listings are not meant as an endorsement by ISCB.



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