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Metadata For Systems Biology

Metadata For Systems Biology

This video was recorded at 3rd International Workshop on Machine Learning in Systems Biology (MLSB), Ljubljana 2009. The ease with which modern computational and theoretical tools can be applied to modeling has led to an exponential increase in the size and complexity of computational models in biology. At the same time, the accelerating pace of progress also highlights limitations in current approaches to modeling. One of these limitations is the insufficient degree to which the semantics and qualitative behaviour of models are systematised and expressed formally enough to support unambiguous interpretation by software systems. As a result, human intervention is required to interpret and connect a model's mathematical structures with information about the its meaning (semantics). Often, this critical information is usually communicated through free-text descriptions or non-standard annotations; however, free-text descriptions cannot easily be interpreted by current modeling tools. We will describe three efforts to standardize the encoding of missing semantics for kinetic models. The overall approach involves connecting model elements to common, external sources of information that can be extended as existing knowledge is expanded and refined. These external sources are carefully managed public, free, consensus ontologies: the Systems Biology Ontology (SBO), the Kinetic Simulation Algorithm Ontology (KiSAO), and the Terminology for the Description of Dynamics (TeDDy). Together they provide a means for annotating a model with stable and perennial identifiers which reference machine readable regulated terms defining the semantics of the three facets of the modeling process 1) the relationship between the model and the biology it aims to describe, 2) the process used to simulate the model and obtain expected results, and 3) the results themselves.


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