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Full-Text Articles in Bioinformatics

Structure-Function Analysis And Characterization Of Metalloproteins., Sen Yao Aug 2016

Structure-Function Analysis And Characterization Of Metalloproteins., Sen Yao

Electronic Theses and Dissertations

Metalloproteins are proteins that can bind at least one metal ion as a cofactor. They utilize metal ions for a variety of biological purposes, and are essential for all domains of life. Due to the ubiquity of metalloprotein’s involvement across these processes across all domains of life, how proteins coordinate metal ions for different biochemical functions is of great relevance to understanding the implementation of these biological processes. One of the most important aspects of metal binding is its coordination geometry (CG), which often implies functional activities. Most of the current studies are based on the assumption of previously reported …


Integrated Analysis Of Mirna/Mrna Expression And Gene Methylation Using Sparse Canonical Correlation Analysis., Dake Yang May 2016

Integrated Analysis Of Mirna/Mrna Expression And Gene Methylation Using Sparse Canonical Correlation Analysis., Dake Yang

Electronic Theses and Dissertations

MicroRNAs (miRNAs) are a large number of small endogenous non-coding RNA molecules (18-25 nucleotides in length) which regulate expression of genes post-transcriptionally. While a variety of algorithms exist for determining the targets of miRNAs, they are generally based on sequence information and frequently produce lists consisting of thousands of genes. Canonical correlation analysis (CCA) is a multivariate statistical method that can be used to find linear relationships between two data sets, and here we apply CCA to find the linear combination of differentially expressed miRNAs and their corresponding target genes having maximal negative correlation. Due to the high dimensionality, sparse …


Expression Of Genes For Peptide/Protein Hormones And Their Cognate Receptors In Breast Carcinomas As Biomarkers Predicting Risk Of Recurrence., Michael Wesley Daniels May 2016

Expression Of Genes For Peptide/Protein Hormones And Their Cognate Receptors In Breast Carcinomas As Biomarkers Predicting Risk Of Recurrence., Michael Wesley Daniels

Electronic Theses and Dissertations

Certain hormones and/or receptors influencing normal cellular pathways were detected in breast cancers. The hypothesis is that gene subsets predict risk of breast carcinoma recurrence in patients with primary disease. Gene expression of 55 hormones and 73 receptors were determined by microarray with LCM-procured carcinoma cells of 247 de-identified biopsies. Univariate and multivariate Cox regressions were determined using expression levels of each hormone/receptor gene, individually or as a pair. Significant genes derived for each subset were analyzed to predict risk of cancer recurrence with 1000 LASSO training/test sets. A 14-gene molecular signature was identified for predicting clinical outcome without regard …