Connectionists: CFP: Probabilistic Modeling and Machine Learning in Structural and Systems Biology

[Esa A Pitkanen]

                           CALL FOR PAPERS
 
                             Workshop on
             Probabilistic Modeling and Machine Learning  
                  in Structural and Systems Biology
 
        http://www.cs.helsinki.fi/group/bioinfo/events/pmsb06/
 
                  Tuusula, Finland, 17-18 June 2006
 

Deadline for submission: April 23, 2006


Motivation
 
The ever-ongoing growth in the amount of biological data, the 
development of  
genome-wide measurement technologies, and the shift from the study of  
individual genes to systems view all contribute to the need to develop  
computational techniques for learning models from data. At the same time,  
the increase in available computational resources has enabled new, more  
realistic modeling methods to be adopted.
 
In bioinformatics, most of the targets of interest deal with complex  
structured objects: sequences, 2D and 3D structures or interaction 
networks.  
In many cases these structures are naturally described by probabilistic  
graphical models, such as Hidden Markov Models, Conditional Random Fields  
or Bayesian Networks. Recently, approaches that combine Support Vector  
Machines and probabilistic models have been introduced (Fisher kernels,  
Max-margin Markov Networks, Structured SVM). These techniques benefit from  
efficient convex optimization approaches and thus are potentially  
well-scalable to large problems in bioinformatics.
 
The increasing amount of high-throughput experimental data begins to 
enable  
the use of these advanced modelling methods in bioinformatics and systems  
biology. At the same time new computational challenges emerge. Statistical  
methods are required to process the data so that underlying potentially  
complex statistical patterns can be discerned from spurious patterns  
created by random effects. At its simplest this problem calls for data  
normalization and statistical hypothesis testing, in the more general 
case,  
one is required to select a model (e.g. gene network) that best explains 
the  
data.
 
Objective
 
The aim of this workshop is to provide a broad look at the state of the 
art  
in the probabilistic modeling and machine learning methods involving  
biological structures and systems, and to bring together method developers  
and experimentalists working with the problems.
 
We encourage submissions bringing forward methods for discovering complex  
structures (e.g. interaction networks, molecule/cellular structures) and  
methods supporting genome-wide data analysis.
 
A non-exhaustive list of topics suitable of this workshop:
 
Methods
 
    * Algorithms
    * Bayesian Methods
    * Data integration/fusion
    * Feature/subspace selection
    * High-throughput methods
    * Kernel Methods
    * Machine Learning
    * Probabilistic Inference
    * Structured output prediction
 
Applications
 
    * Sequence Annotation
    * Gene Expression
    * Gene Networks
    * Gene Prediction
    * Metabolic Profiling
    * Metabolic Reconstruction
    * Protein Structure Prediction
    * Protein Function Prediction
    * Protein-protein interaction networks
 
The workshop is organized by the European Network of Excellence PASCAL  
(Pattern Analysis, Statistical Modelling and Computational Learning) and  
belongs to the thematic programme on 'Learning with Complex and Structured  
Outputs'.
 
The workshop is immediately followed by the International Specialised  
Symposium on Yeasts (ISSY25, June 18-21 2006) that has the theme 'Systems  
biology of Yeast - From Models to Applications'.
 
 
Submissions
 
We invite to submit an extended abstract of maximum four pages, formatted
according to the Springer Lecture Notes in Computer Science style, to
the email address juho.rousu at cs.helsinki.fi
 
Selected papers from the workshop will be published in BMC Bioinformatics
special issue. BMC Bioinformatics has impact factor 5.42, which makes it 
the
second highest ranked bioinformatics journal.
 
 
Important dates
 
    * April 23, 2006: Abstract submission deadline
    * May 7, 2006: Notification of acceptance
    * May 31, 2006: Final version due
    * June 17-18, 2006: Workshop
 
Invited Speakers (confirmed)
 
    * Tommi Jaakkola, MIT
    * Koji Tsuda, CBRC / AIST, Japan
 
Organizing Committee
 
    * Florence d'Alché-Buc, Université d'Evry-Val d'Essonne
    * Jaakko Astola, Tampere University of Technology
    * Nello Cristianini, UC Davis / University of Bristol
    * Liisa Holm, University of Helsinki
    * Mark Girolami, University of Glasgow
    * Samuel Kaski, Helsinki University of Technology
    * Matej Oresic, Technical Research Centre of Finland
    * Juho Rousu, University of Helsinki
    * Esko Ukkonen, Helsinki Institute for Information Technology
    * Jean-Philippe Vert, Ecole des Mines de Paris
 
Local Organization
 
    * Juho Rousu, University of Helsinki
    * Samuel Kaski, Helsinki University of Technology
    * Esko Ukkonen, Helsinki Institute for Information Technology
    * Esa Pitkänen, University of Helsinki, workshop secretary  
 
Location
 
    * The workshop will be held in Conference Hotel Gustavelund, 15 minute  
      trip from Helsinki-Vantaa airport.  

-------------- next part --------------
                           CALL FOR PAPERS

                             Workshop on
             Probabilistic Modeling and Machine Learning 
                in Structural and Systems Biology

      http://www.cs.helsinki.fi/group/bioinfo/events/pmsb06/

                 Tuusula, Finland, 17-18 June 2006

Motivation

The ever-ongoing growth in the amount of biological data, the development of 
genome-wide measurement technologies, and the shift from the study of 
individual genes to systems view all contribute to the need to develop 
computational techniques for learning models from data. At the same time, 
the increase in available computational resources has enabled new, more 
realistic modeling methods to be adopted.

In bioinformatics, most of the targets of interest deal with complex 
structured objects: sequences, 2D and 3D structures or interaction networks. 
In many cases these structures are naturally described by probabilistic 
graphical models, such as Hidden Markov Models, Conditional Random Fields 
or Bayesian Networks. Recently, approaches that combine Support Vector 
Machines and probabilistic models have been introduced (Fisher kernels, 
Max-margin Markov Networks, Structured SVM). These techniques benefit from 
efficient convex optimization approaches and thus are potentially 
well-scalable to large problems in bioinformatics.

The increasing amount of high-throughput experimental data begins to enable 
the use of these advanced modelling methods in bioinformatics and systems 
biology. At the same time new computational challenges emerge. Statistical 
methods are required to process the data so that underlying potentially 
complex statistical patterns can be discerned from spurious patterns 
created by random effects. At its simplest this problem calls for data 
normalization and statistical hypothesis testing, in the more general case, 
one is required to select a model (e.g. gene network) that best explains the 
data.

Objective

The aim of this workshop is to provide a broad look at the state of the art 
in the probabilistic modeling and machine learning methods involving 
biological structures and systems, and to bring together method developers 
and experimentalists working with the problems.

We encourage submissions bringing forward methods for discovering complex 
structures (e.g. interaction networks, molecule/cellular structures) and 
methods supporting genome-wide data analysis.

A non-exhaustive list of topics suitable of this workshop:

Methods

    * Algorithms
    * Bayesian Methods
    * Data integration/fusion
    * Feature/subspace selection
    * High-throughput methods
    * Kernel Methods
    * Machine Learning
    * Probabilistic Inference
    * Structured output prediction

Applications

    * Sequence Annotation
    * Gene Expression
    * Gene Networks
    * Gene Prediction
    * Metabolic Profiling
    * Metabolic Reconstruction
    * Protein Structure Prediction
    * Protein Function Prediction
    * Protein-protein interaction networks

The workshop is organized by the European Network of Excellence PASCAL 
(Pattern Analysis, Statistical Modelling and Computational Learning) and 
belongs to the thematic programme on 'Learning with Complex and Structured 
Outputs'.

The workshop is immediately followed by the International Specialised 
Symposium on Yeasts (ISSY25, June 18-21 2006) that has the theme 'Systems 
biology of Yeast - From Models to Applications'.


Submissions

We invite to submit an extended abstract of maximum four pages, formatted
according to the Springer Lecture Notes in Computer Science style, to
the email address juho.rousu at cs.helsinki.fi

Selected papers from the workshop will be published in BMC Bioinformatics
special issue. BMC Bioinformatics has impact factor 5.42, which makes it the
second highest ranked bioinformatics journal.


Important dates

    * April 23, 2006: Abstract submission deadline
    * May 7, 2006: Notification of acceptance
    * May 31, 2006: Final version due
    * June 17-18, 2006: Workshop

Invited Speakers (confirmed)

    * Tommi Jaakkola, MIT
    * Koji Tsuda, CBRC / AIST, Japan

Organizing Committee

    * Florence d'Alché-Buc, Université d'Evry-Val d'Essonne
    * Jaakko Astola, Tampere University of Technology
    * Nello Cristianini, UC Davis / University of Bristol
    * Liisa Holm, University of Helsinki
    * Mark Girolami, University of Glasgow
    * Samuel Kaski, Helsinki University of Technology
    * Matej Oresic, Technical Research Centre of Finland
    * Juho Rousu, University of Helsinki
    * Esko Ukkonen, Helsinki Institute for Information Technology
    * Jean-Philippe Vert, Ecole des Mines de Paris

Local Organization

    * Juho Rousu, University of Helsinki
    * Samuel Kaski, Helsinki University of Technology
    * Esko Ukkonen, Helsinki Institute for Information Technology
    * Esa Pitkänen, University of Helsinki, workshop secretary 

Location

    * The workshop will be held in Conference Hotel Gustavelund, 15 minute 
      trip from Helsinki-Vantaa airport.