Communities in biology have developed a number of ontologies that provide standard terminologies for the
characteristics of various concepts and their relationships. However, it is difficult to construct and maintain such
ontologies in biology, since it is a non-trivial task to identify commonly used potential member terms in a particular
ontology, in the presence of constant changes of such terms over time as the research in the field advances. In this paper,
we propose a visualization system, called BioTermViz, which presents the temporal distribution of ontological terms
from the text of published journal abstracts. BioTermViz shows such a temporal distribution of terms for journal
abstracts in the order of published time, occurrences of the annotated Gene Ontology concepts per abstract, and the
ontological hierarchy of the terms. With a combination of these three types of information, we can capture the global
tendency in the use of terms, and identify a particular term or terms to be created, modified, segmented, or removed,
effectively developing biological ontologies in an interactive manner. In order to demonstrate the practical utility of
BioTermViz, we describe several scenarios for the development of an ontology for a specific sub-class of proteins, or
ubiquitin-protein ligases.
Data sets of up to 3000 journal abstracts from MEDLINE literature on
the keyword combination `MAPK pathway' and `human' are visualized and
analyzed for mitogen-activated protein kinase (MAPK) pathways. We have
tightly coupled exploratory visualization with information extraction for interactive navigation through scattered information sources, in search of useful facts on MAPK by frequency-based filtering and
amplification. Unlike direct database visualization that operates on
curated data sets, literature visualization has the advantages of
manipulating data sets of a massive scale with a lot less manpower and
effectively responding to the fast cycles of the developments in the
field.
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