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Full-Text Articles in Biomedical Engineering and Bioengineering

An Algorithm For Optimally Fitting A Wiener Model, Lucas P. Beverlin, Derrick K. Rollins Sr., Nisarg Vyas, David Andre Jan 2011

An Algorithm For Optimally Fitting A Wiener Model, Lucas P. Beverlin, Derrick K. Rollins Sr., Nisarg Vyas, David Andre

Chemical and Biological Engineering Publications

The purpose of this work is to present a new methodology for fitting Wiener networks to datasets with a large number of variables. Wiener networks have the ability to model a wide range of data types, and their structures can yield parameters with phenomenological meaning. There are several challenges to fitting such a model: model stiffness, the nonlinear nature of a Wiener network, possible overfitting, and the large number of parameters inherent with large input sets. This work describes a methodology to overcome these challenges by using several iterative algorithms under supervised learning and fitting subsets of the parameters at ...


An Extended Data Mining Method For Identifying Differentially Expressed Assay-Specific Signatures In Functional Genomic Studies, Derrick K. Rollins Sr., Ai-Ling Teh Jan 2010

An Extended Data Mining Method For Identifying Differentially Expressed Assay-Specific Signatures In Functional Genomic Studies, Derrick K. Rollins Sr., Ai-Ling Teh

Chemical and Biological Engineering Publications

Background: Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and ...