Pathway data mining: tissue specificity and potential cross talks between pathwaysYu-Tai Wang1, Ueng-Cheng Yang2, Yung-Wen Deng, Cheng-Min Wei, Kai-Lung Tang, Der-Ming Liou.
firstname.lastname@example.org, Institute of Biochemistry, National Yang-Ming University, Taiwan; email@example.com, Bioinformatics Research Center, National Yang-Ming University, Taiwan
Most of the molecular, cellular, and developmental biology researches focus on studying the mechanism behind a biological phenomenon. The center of the above researches is thus a pathway-discovery and a pathway interaction problem. This work focused on discovering novel pathways from available information. Although pathway studies were performed in a given cell line, the users tend to extrapolate this information to other types of cells. We have used the library information of expressed sequence tag to annotate the tissue specificity of a given pathway. For example, many tissues can accept growth signal from both EGF and PDGF, but the others can only accept signal from either EGF or PDGF. Besides, the fasPathway and p38mapk Pathway in BioCarta collection (http://www.biocarta.com/genes/index.asp) may have cross talks based on TRADD and FADD interaction. However, this hypothesis will not be true unless both pathways are expressed in the same tissue and at the same time. Even though the expression time information is difficult to get, both pathways are expressed in human brain. In other words, the tissue information supports possible cross talks between pathways. Since the cross talk between pathways will not show up in known maps, a program is required to present the cross talk graphically. We have used GraphViz tool kit (http://www.research.att.com/sw/tools/graphviz/) to display the database query results.