@article {1973211,
	title = {User-Centered Evaluation of Arizona BioPathway: An Information Extraction, Integration, and Visualization System},
	journal = {IEEE Transactions on Information Technology in Biomedicine},
	volume = {11},
	year = {2007},
	month = {2007},
	pages = {527-536},
	abstract = {Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This article presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature viewing method. Relation aggregation significantly contributes to knowledge acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multi-view, relation-based interface which supports user-controlled exploration of pathway information across multiple granularities.},
	keywords = {Accounting, BIS},
	url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=4300830\&arnumber=4300844\&count=17\&index=5},
	author = {Qui{\~n}ones,Karin  D. and Su,Hua and Marshall,Byron and Eggers,Shauna and Chen,Hsinchun}
}
@article {1973221,
	title = {Aggregating Automatically Extracted Regulatory Pathway Relations},
	journal = {IEEE Transactions on Information Technology in Biomedicine},
	volume = {10},
	year = {2006},
	month = {2006},
	pages = {100- 108},
	abstract = {Automatic tools to extract information from biomedical texts are needed to help researchers leverage the vast and increasing body of biomedical literature. While several biomedical relation extraction systems have been created and tested, little work has been done to meaningfully organize the extracted relations. Organizational processes should consolidate multiple references to the same objects over various levels of granularity, connect those references to other resources, and capture contextual information. We propose a feature decomposition approach to relation aggregation to support a five-level aggregation framework. Our BioAggregate tagger uses this approach to identify key features in extracted relation name strings. We show encouraging feature assignment accuracy and report substantial consolidation in a network of extracted relations.},
	keywords = {Accounting, BIS},
	url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_IEEE_TITB_2005.pdf},
	author = {Marshall,Byron and Su,Hua and McDonald,Daniel and Eggers,Shauna and Chen,Hsinchun}
}
@conference {1984611,
	title = {Visualizing Aggregated Biological Pathway Relations},
	booktitle = {Proceedings of the 2005 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2005), June 7-11, 2005 , Denver, CO},
	year = {2005},
	month = {2005},
	abstract = {The Genescene development team has constructed an aggregation interface for automatically-extracted biomedical pathway<br>relations that is intended to help researchers identify and process relevant information from the vast digital library of abstracts found in the National Library of Medicine{\textquoteright}s PubMed collection.<br>Users view extracted relations at various levels of relational granularity in an interactive and visual node-link interface. Anecdotal feedback reported here suggests that this multigranular visual paradigm aligns well with various research tasks,<br>helping users find relevant articles and discover new information.},
	keywords = {Accounting, BIS},
	url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_JCDL_2005_Aggregation.pdf},
	author = {Marshall,Byron and Qui{\~n}ones,Karin and Su,Hua and Eggers,Shauna and Chen,Hsinchun}
}