Interdisciplinary Bio Central
 
Etc. (Medical informatics)

Visualization for Digesting a High Volume of the Biomedical Literature
Changsu Lee1, Jinah Park2 and Jong C. Park1,*
1KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon, South KOREA
2ICU (Information and Communications University), 119 Munjiro, Yuseong-gu, Daejeon, South KOREA
*Corresponding author
  Published : February 28, 2006
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Synopsis

The paradigm in biology is currently changing from that of conducting hypothesis-driven individual experiments to that of utilizing the results of a massive data analysis with appropriate computational tools. We present LayMap, an implemented visualization system that helps the user to deal with a high volume of the biomedical literature such as MEDLINE, through the layered maps that are constructed on the results of an information extraction system. LayMap also utilizes filtering and granularity for an enhanced view of the results. Since a biomedical information extraction system gives rise to a focused and effective way of slicing up the data space, the combined use of LayMap with such an information extraction system can help the user to navigate the data space in a speedy and guided manner. As a case study, we have applied the system to datasets of journal abstracts on 'MAPK pathway' and 'bufalin' from MEDLINE. With the proposed visualization, we have successfully rediscovered pathway maps of a reasonable quality for ERK, p38 and JNK. Furthermore, with respect to bufalin, we were able to identify the potentially interesting relation between the Chinese medicine Chan su and apoptosis with a high level of detail.

Keyword: visualization, information extraction, biomedical literature
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