Integrative Bioinformatics 2007, Day 2: MIN to ODEs, Yartseva et al

Other than where specified, these are my notes from the IB07 Conference, and not expressions of opinion. Any errors are probably just due to my own misunderstanding. :)

From MIN model to ordinary differential equations. A MIN model is a knowledge management formalism for biology. A model should enable knowledge integration, hyp testing, prediction of response, and discovery of fundamental processes.

MIN has: universality (the integratin of various kinds of bio data available today), parsimony (the simplest possible representation of the data), incrementality ( construction of more complex models from simpler ones), precision (expression of relations in a non-ambiguous mathematical way), transposability (formal rules for the translation of the information contained in the model into commonly used (target) modelling formalisms). MIN improves the MIB model: it is a bi-partite graph with labelled nodes and arcs.

Putting microscopic and macroscopic data together. In an example, she describes relation "F", which enumerates the experimentally observed system states expressed through the variables' values. Translation into multivalued logical formalism: the translation procedure produces the candidate models for further analysis. Then there is a direct translation into ODEs.

Note: I lost my way about here, but it sounded really interesting nonetheless. Refer to the paper for more details.