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Call for papers

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 (probabilistic logic models, Bayesian methods, etc). These methods are well-suited for this application area, since the available data is highly complex and tends to have a significant amount of missing information.

The workshop aims at bringing together researchers from both the field of relational learning, machine learning over structured data and biology. We therefore invite submissions that describe new methods, problem settings, applications and models, exploiting structured data in the field of biology. Methods include, but are not restricted to

  • Statistical Relational Learning
  • Relational Probabilistic Models
  • Inductive Logic Programming
  • Multi-relational Data Mining
  • Graph Methods
The data, structures or models considered can include but are not limited to
  • Sequences (DNA, RNA, protein)
  • Pathways (chemical, metabolic, mutation, interaction pathways)
  • 2D, 3D structures of proteins, RNA
  • Chemical structures (e.g. QSAR, especially regarding interaction of compounds with proteins)
  • Evolutionary relations (phylogeny, homology relations)
  • Ontologies integration (gene, enzyme, protein function ontologies)
  • Large networks (regulatory, co-expression, interaction, and metabolic networks)
  • Concept graphs (including compounds, articles, authors, references)

Submission Guidelines

  • Page limit for papers: 8 pages
  • Formatting: Submitted papers should be formatted according to the Springer-Verlag Lecture Notes in Artificial Intelligence guidelines. Authors' instructions and style files can be downloaded from http://www.springer.de/comp/lncs/authors.html
  • Papers can be submitted by E-mail to the following address: strebio08@cs.kuleuven.be
Note that, as for all the ECML Workshops, accepted papers will be printed in the informal proceedings and made available at the time of the Workshop.