Structuring Mined Knowledge for the Support of Hypothesis Generation in Molecular Biology
نویسندگان
چکیده
Hypothesis generation in the life sciences is an empirical process in which obtaining and structuring knowledge from literature plays a significant role. Text mining and Information Extraction techniques are seen as key for programmatically accessing the knowledge captured in the form of free text. We describe progress towards an application that supports the task of generating a hypothesis about biomolecular mechanisms using Semantic Web technologies and a workflow to carry out text mining in a service-oriented architecture. The output is a semantic model with putative biological relationships that have been extracted from literature, with each relationship linked to the corresponding evidence. We present preliminary data that extends a model for chromatin (de)condensation. The methodology can be used to bootstrap the process of human-guided construction of semantically rich biological models using the results of knowledge extraction processes.
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