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Full-Text Articles in Life Sciences
Cross-Ontology Multi-Level Association Rule Mining In The Gene Ontology., Prashanti Manda, Seval Ozkan, Hui Wang, Fiona M. Mccarthy, Susan M. Bridges
Cross-Ontology Multi-Level Association Rule Mining In The Gene Ontology., Prashanti Manda, Seval Ozkan, Hui Wang, Fiona M. Mccarthy, Susan M. Bridges
Bagley College of Engineering Publications and Scholarship
The Gene Ontology (GO) has become the internationally accepted standard for representing function, process, and location aspects of gene products. The wealth of GO annotation data provides a valuable source of implicit knowledge of relationships among these aspects. We describe a new method for association rule mining to discover implicit co-occurrence relationships across the GO sub-ontologies at multiple levels of abstraction. Prior work on association rule mining in the GO has concentrated on mining knowledge at a single level of abstraction and/or between terms from the same sub-ontology. We have developed a bottom-up generalization procedure called Cross-Ontology Data Mining-Level by …
Fecal Near Infrared Spectroscopy To Discriminate Physiological Status In Giant Pandas., Erin E. Wiedower, Andrew J. Kouba, Carrie K. Vance, Rachel L. Hansen, Jerry W. Stuth, Douglas R. Tolleson
Fecal Near Infrared Spectroscopy To Discriminate Physiological Status In Giant Pandas., Erin E. Wiedower, Andrew J. Kouba, Carrie K. Vance, Rachel L. Hansen, Jerry W. Stuth, Douglas R. Tolleson
College of Agriculture & Life Sciences Publications and Scholarship
Giant panda (Ailuropoda melanoleuca) monitoring and research often require accurate estimates of population size and density. However, obtaining these estimates has been challenging. Innovative technologies, such as fecal near infrared reflectance spectroscopy (FNIRS), may be used to differentiate between sex, age class, and reproductive status as has been shown for several other species. The objective of this study was to determine if FNIRS could be similarly used for giant panda physiological discriminations. Based on samples from captive animals in four U.S. zoos, FNIRS calibrations correctly identified 78% of samples from adult males, 81% from adult females, 85% from adults, 89% …