Dept. of Biomedical Informatics
Oregon Health & Science University
The emphasis of multilevel modeling techniques in the Neurosciences has led to an increased need for large-scale databases containing neuroscientific data. Despite this, such databases are not being populated at a rate commensurate with their demand amongst Computational Neuroscientists. The reasons for this are common to scientific database curation in general--limitation of resources. Much of Neuroscience's long tradition of research has been documented in computationally inaccessible formats, such as the pdf, making large-scale data extraction laborious and expensive. Here we present three sets of studies designed to construct automated tools for alleviating three bottlenecks in the workflow of a community-curated knowledge base of neuroscience-related information. Virk, the first of these tools, is designed specifically with under-developed knowledge bases in mind, using active learning to allow them to quickly bootstrap their development. Flokka, our second tool, is designed for p
School of Medicine
Ambert, Kyle H., "Text-mining tools for optimizing community database curation workflows in neuroscience" (2013). Scholar Archive. 896.