ECML PKDD 2008

The workshop will be held in room R004
in the R building

Challenges in relational and probabilistic data mining: a peptidomics case study.

Peptidomics is (by analogy with other “-omics” like genomics and proteomics) the systematic study of the complete set of (endogenous) peptides of an organism, tissue, cell, or organelle and its changes in space and time under different conditions. Endogenous peptides play a critical role as signaling molecules in most biological systems and their disturbance underlies many disease processes.

Developing Robust Synthetic Biology designs using a Microfluidic Robot Scientist

Synthetic Biology is an emerging discipline that is providing a conceptual framework for biological engineering based on principles of standardisation, modularity and abstraction. For this approach to achieve the ends of becoming a widely applicable engineering discipline it is critical that the resulting devices are capable of functioning according to a given specification in a robust fashion.

We are happy to announce the following keynote speakers at the StReBio'08 workshop;

• Stephen Muggleton (Imperial college), one of the founders of inductive logic programming, author of the logical probabilistic representation language "Stochastic Logic Programs", and currently active in the field of molecular biology with a wide range of applications, including chemo-informatics and protein structure prediction.

Questions about the workshop and submissions should be sent to strebio08@cs.kuleuven.be

Organizing Committee:

• Jan Ramon, K.U. Leuven,
• Fabrizio Costa, K.U. Leuven,
• Christophe Costa Flor\^{e}ncio, K.U. Leuven,
• Joost Kok, Leiden Institute of Advanced Computer Science,

Program Committee

• Andreas Bender (Leiden/Amsterdam Center for Drug Research, Netherlands)
• Paolo Frasconi (University of Florence, Florence, Italy)
• Amanda Clare (University of Aberystwyth, UK)
• Yves Moreau (ESAT, K.U.Leuven, Belgium)

Call for Problem statements

We invite biological problem statements from the fields of biology and bioinformatics.

Modern experimentation and data acquisition techniques allow the study of complex interactions in biological systems, but yield very large quantities of data. This raises interesting challenges as how to analyze, interpret and exploit the data.

The field of data mining and machine learning is concerned with algorithms to analyze data, the automatic discovery of useful patterns and insights, and the exploitation of the acquired knowledge to

There is an increasing interest for structured data in the machine learning community as shown by the growing number of dedicated Conferences and Workshops (MLG, SRL, ILP, MRDM). Bioinformatics is an application domain of increasing popularity where information is naturally represented in terms of relations between (possibly heterogeneous) objects.

The Workshop on Relational Learning in Bioinformatics focuses on learning methods for structured biological data (relational data, graphs, logic based descriptions, etc) in the presence of uncertainty

You can download the papers from the paper list

10:30-11:20	Invited speaker: Stephen Muggleton: Developing Robust Synthetic Biology designs using a Microfluidic Robot Scientist (abstract)
11:20-11:40	Henning Christiansen and Ole Torp Lassen: Optimization and Evaluation of Probabilistic-Logic Sequence Models
11:

Bioinformatics is an application domain where information is naturally represented in terms of relations between heterogenous objects. Modern experimentation and data acquisition techniques allow the study of complex interactions in biological systems. This raises interesting challenges for machine learning and data mining researchers, as the amount of data is huge, some information can not be observed, and measurements may be noisy.