NO.010 International Symposium on Symbolic Systems Biology
November 14 - 17, 2011 (Check-in: November 13, 2011 )
- Prof. Katsuhisa Horimoto
- Institute of Advanced Industrial Science and Technology, Japan
- Prof. Katsumi Inoue
- National Institute of Informatics, Japan
- Dr. Oliver Ray
- University of Bristol, UK
Symbolic Systems Biology is a growing area of research involving the application of formal logic-based methods to systems biology and bioinformatics. With biological data being acquired at ever increasing rates, purely numerical techniques must be combined with symbolic approaches in order to help formalize expert knowledge and integrate information across different levels of biological abstraction. Recently, a number of symbolic approaches have been developed and usefully applied to a variety of biological problems. Such methods include formal logics (e.g., propositional/first-order/modal frameworks), computational logics (e.g., constraint/logic/answer-set programs), graphical models (e.g., Boolean/Bayesian/Petri nets), synthetic inference (abduction/induction), formal methods (e.g., model checking/pi-calculus/hybrid logic), qualitative reasoning, action languages, and statistical relational learning.
But, currently, there is an urgent need for a methodical comparison of these existing symbolic systems biology approaches and the types of biological problems to which they have been applied. This is necessary to understand the strengths and weaknesses of each approach and the characteristic features of their respective applications. Such a study would help to facilitate research in symbolic systems biology by providing a roadmap of which systems are best suited to which problems and allowing more effective exploitation and re-use of algorithms and data.
At the same time, there is also a need for more collaboration between numerical and symbolic biologists. This is necessary to better understand the advantages and drawbacks of the quantitative and qualitative approaches and progress towards a synergistic integration of the two. Ideally this should be done with advice from experimental biologists who are better informed of hot applications and emerging methods of data acquisition. This will help to provide a real context in which symbolic systems biology can be more usefully developed.
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