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Post date: Jun 10, 2014 8:29:36 AM
Workshop: "Statistical Methods for Omics Data Integration and
Analysis"
Heraklion, Crete, Greece, November 10-12, 2014
Host and Venue: Foundation for Research and Technology, Hellas
Important Dates:
20/08/2014 Abstract Submission Deadline
10/09/2014 Abstract Notifications
15/09/2014 Early Registration Deadline
10/11/2014 – 12/11/2014 Workshop Dates
Objectives:
This workshop aims to bring together researchers in the fields of
biology, bioinformatics, computational biology, statistics,
biostatistics, machine learning, data mining, and pattern recognition
that work on the analysis of omics data (e.g., transcriptomics,
metabolomics, genomics) and particularly researchers that focus on
developing new methods of integrating data, integrating their
visualization, and integrating analysis of multiple and heterogeneous
datasets. More details of the objectives of the workshop are here .
Programme:
The Workshop Programme consists of invited talks by prominent
researchers in the field, presentations of extended abstracts, poster
presentations, and social events.
Keynote Speakers:
A panel of prominent keynote speakers will present in the workshop:
- John Storey , Princeton University
- Michael Stumpf, Imperial College
- Andrew Teschendorff, UCL, London
- Sven Nelander, Uppsala University
In addition, the workshop will be attended by most STATegra partners.
Organized by: the STATegra consortium
STATegra (stategra.eu) is an FP7 European project. The STATegra project
aims to develop new statistical methods and tools for the integrative
analysis of diverse omics data for a more efficient use of the genomics
technologies. Furthermore we aim to make them readily available to the
research community through rapid and efficient implementation as
user-friendly software packages. Among the data-types we consider:
mRNA-seq, miRNA-seq, Methyl-seq, Chip-seq, DNase-seq, Proteomics and
Metabolomics. In addition we will develop methods for data gathering,
management and integration in Knowledge Databases and Ontologies. We
will deliver statistical methodologies to generalize meta-analysis of
heterogeneous datasets (e.g., different experimental conditions) to
address the issues of values missing-by-design, limited availability,
poor quality (“dirty”) data and individually insufficiently powered
studies.
STATegra partners supporting the Workshop are:
-CLC bio (Denmark)
-Biomax Informatics AG (Germany)
-Karolinska Institutet (Sweden)
-Imperial College of Science, Technology and Medicine (UK)
-Foundation for Research and Technology – Hellas (Greece)
-Institut d’Investigació Biomèdica de Bellvitge (Spain)
-University of Amsterdam (Holland)
-University of Leiden (Holland)
-Τhe Ludwig-Maximilians University of Munich (Germany)
-University of California (USA)
-Genomic of the Gene Expression Lab, Principe Felipe Research
Centre (CIPF) (Spain)
Organizing & Scientific Program Committee:
-Ana Conesa, CIPF
-David Gómez-Cabrero, Karolinska Institutet
-Dieter Maier, Biomax
-Veronica von Saint Paul, Biomax
-Amanda Fisher, Imperial College London
-Jesper Tegnér , Karolinska Institute
-Ioannis Tsamardinos , FORTH
-Johan Westerhuis, University of Amsterdam
-Matthias Merkenschlager, Imperial College London
-Roald Forsberg, CLC bio
-Michael Lappe, CLC bio
-Vincenzo Lagani, FORTH
Submission:
We solicit papers with particular focus to the following areas:
-Methods for retrieving related omics data, integrate them, and
integratively visualize them
-Methods for integrative knowledge discovery from multiple omics
sources and biological knowledge
-Methods for integratively analyzing multiple omics datasets and
biological knowledge. The datasets may be obtained on the same or
matched biological samples but employing different omics technologies
and datasets obtained on different biological samples
-Causal discovery methods for multiple omics datasets
-Methods for integration and integrative analysis of time-course
omics data
-Methods for integrative network analysis stemming from multiple
omics data and biological knowledge-bases
-Innovative applications of statistical, machine learning, and
data mining methods to multiple omics datasets and knowledge bases
-Methods for interpretation and explanation of results obtained
from various omics datasets and knowledge bases
The submissions should be 2-page abstracts. The Program Committee of
the workshop will select a set of abstract to invite for expansion and
inclusion in an Edited Volume in a high-impact journal (under
negotiation). For abstract formats and submission instructions see the
workshop site smodia2014.com
All aspects of the submission process will be handled online via the
EasyChair Conference System at:
https://www.easychair.org/account/signin.cgi?key=11260915.R5ih2MfiVMi1Uw2r
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