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Workshop: "Statistical Methods for Omics Data Integration and Analysis"

posted Jun 10, 2014, 1:29 AM by Georgios Pavlopoulos
Workshop: "Statistical Methods for Omics Data  Integration and 

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
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 .
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 ( 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 

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
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

All aspects of the submission process will be handled online via the 
EasyChair Conference System at: