Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Hierarchical Multi-Label Classification For Protein Function Prediction Going Beyond Traditional Approaches, Noor Al Aydie
Hierarchical Multi-Label Classification For Protein Function Prediction Going Beyond Traditional Approaches, Noor Al Aydie
Wayne State University Dissertations
Hierarchical multi-label classification is a variant of traditional classification in which the
instances can belong to several labels, that are in turn organized in a hierarchy. Functional classification of genes is a challenging problem in functional genomics due to several reasons. First, each gene participates in multiple biological activities. Hence, prediction models should support multi-label classification. Second, the genes are organized and classified according to a hierarchical classification scheme that represents the relationships between the functions of the genes. These relationships should be maintained by the prediction models. In addition, various bimolecular data sources, such as gene expression data and …
Differential Modeling For Cancer Microarray Data, Omar Odibat
Differential Modeling For Cancer Microarray Data, Omar Odibat
Wayne State University Dissertations
Capturing the changes between two biological phenotypes is a crucial task in understanding the mechanisms of various diseases. Most of the existing computational approaches depend on testing the changes in the expression levels of each single gene individually. In this work, we proposed novel computational approaches to identify the differential genes between two phenotypes. These approaches aim to quantitatively characterize the differences between two phenotypes and can provide better insights and understanding of various diseases. The purpose of this thesis is three-fold. Firstly, we review the state-of-the-art approaches for differential analysis of gene expression data.
Secondly, we propose a novel …