Symbolic Systems Biology is a rapidly emerging field involving the application of formal logic-based methods to Systems Biology and Bioinformatics. In contrast to traditional numerical methods, symbolic techniques offer the advantages of being able to directly formalise and exploit biological knowledge in a way that facilitates integration of data across different levels of biological abstraction. Last year saw major developments in this field with the release of a new book and the convening of a first international symposium:

• Symbolic Systems Biology: Theory and Methods
  M.S. Iyengar (Editor), 2011
• The First International Symposium on Symbolic Systems Biology: Approaches and Applications
  O. Ray, K. Inoue, and K. Horimoto (Chairs), 2011

As a result of these developments, it is becoming clear that several symbolic approaches can be usefully deployed in various biological applications - especially in those where information is stored in graph-based formalisms (such as metabolic networks, signalling pathways, genetic interactions, and food webs). Such techniques include

• formal logics (e.g., Boolean, classical and modal logics)
• computational logic (e.g., constraint, answer set and logic programming)
• graphical models (e.g., Bayes and Petri Nets)
• synthetic inference (e.g., abductive, inductive and analogical reasoning)
• formal methods (e.g., model checking, pi-calculus and hybrid logic)
• qualitatitive reasoning and equation discovery

The main aim of the workshop is to explore how machine learning and knowledge discovery techniques can be used within such formalisms in order to further the practical utility of Symbolic Systems Biology. In principle, the ability to support diverse modes of logical inference ought to constitute a major advantage of symbolic methods that would allow them to add significant value over purely numerical methods. The Workshop will aim to explore the theoretical and practical aspects of this claim. Specific topics of interest include

• theory and practice of machine learning and knowledge discovery for symbolic systems biology
• integration of numerical and symbolic techniques
• abductive and inductive hypothesis generation and evaluation
• real-world applications and/or theoretical developments
• methods for biological network repair and reconstruction
• applications of forward, backward, and meta-reasoning

A secondary aim is to identify ways in which purely symbolic methods have been or could be combined with numerical techniques and applied to emerging problems in experimental and synthetic biology. We believe it is important to promote a dialogue between qualitative and quantitative practitioners in order to better handle real world noise and uncertainty. Within the context of machine learning, this raises the issue of how to combine structural and parameter learning.

Finally, we wish to provide a forum to discuss recent developments within symbolic system biology that enhance the power or usability of its constituent approaches. We especially welcome any efforts to make symbolic systems biology more accessible and useful to biologists with no specific background in formal methods.

Submissions should be made through EasyChair system through this link.

The pre-workshop proceedings are available as a PDF

Registration should be made through the ECML PKDD 2012 conference site at this link. As with all workshops at this event, participants will need to register for the main conference.