Open Access. Powered by Scholars. Published by Universities.®

Databases and Information Systems Commons™

Open Access. Powered by Scholars. Published by Universities.®

University of Nebraska - Lincoln

2012

Articles 1 - 3 of 3

Full-Text Articles in Databases and Information Systems

Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi Dec 2012

Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi

CSE Conference and Workshop Papers

Data mining of protein databases poses special challenges because many protein databases are non- relational whereas most data mining and machine learning algorithms assume the input data to be a type of rela- tional database that is also representable as an ARFF file. We developed a method to restructure protein databases so that they become amenable for various data mining and machine learning tools. Our restructuring method en- abled us to apply both decision tree and support vector machine classifiers to a pancreatic protein database. The SVM classifier that used both GO term and PFAM families to characterize proteins gave …

Go to article

Data Mining Of Protein Databases, Christopher Assi Jul 2012

Data Mining Of Protein Databases, Christopher Assi

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Data mining of protein databases poses special challenges because many protein databases are non-relational whereas most data mining and machine learning algorithms assume the input data to be a relational database. Protein databases are non-relational mainly because they often contain set data types. We developed new data mining algorithms that can restructure non-relational protein databases so that they become relational and amenable for various data mining and machine learning tools. We applied the new restructuring algorithms to a pancreatic protein database. After the restructuring, we also applied two classification methods, such as decision tree and SVM classifiers and compared their …

Go to article

An Approach To The Virtual Flora Of Mongolia – From A Data Repository To An Expert System, Http://Greif.Uni-Greifswald.De/Floragreif/, Jörg Hartleib, Martin Schnittler, Sabrina Rilke, Anne Zemmrich, Bernd Bobertz, Ulrike Najmi, Reinhard Zölitz, Susanne Starke Jan 2012

An Approach To The Virtual Flora Of Mongolia – From A Data Repository To An Expert System, Http://Greif.Uni-Greifswald.De/Floragreif/, Jörg Hartleib, Martin Schnittler, Sabrina Rilke, Anne Zemmrich, Bernd Bobertz, Ulrike Najmi, Reinhard Zölitz, Susanne Starke

Erforschung biologischer Ressourcen der Mongolei / Exploration into the Biological Resources of Mongolia, ISSN 0440-1298

FloraGREIF is an internet accessible information system providing taxonomic, phytogeographic and ecological information on Mongolia’s flora in terms of descriptions, high-resolution plant images and an interactive WebGIS application. Organised along an updated checklist of the approx. 3000 Mongolian vascular plants that serves as a taxonomic backbone, information is split into the taxon level, referring to plant species, and the record level, referring to record or a collected plant specimen. At the latter level, images of living plants, scans of herbarium sheets, habitat photos and further notes can be found. Both data levels are linked by the name of the respective …

Go to article