Relationship between gene co-expression and probe localization on microarray slides

Background  

Microarray technology allows simultaneous measurement of thousands of genes in a single experiment. This is a potentially useful tool for evaluating co-expression of genes and extraction of useful functional and chromosomal structural information about genes.     

Chromosomal loci important for cotyledon opening under UV-B in Arabidopsis thaliana

Background  

Understanding of the genetic architecture of plant UV-B responses allows extensive targeted testing of candidate genes or regions, along with combinations of those genes, for placement in metabolic or signal transduction pathways.     

A hierarchical statistical model for estimating population properties of quantitative genes

Background  

Earlier methods for detecting major genes responsible for a quantitative trait rely critically upon a well-structured pedigree in which the segregation pattern of genes exactly follow Mendelian inheritance laws. However, for many outcrossing species, such pedigrees are not available and genes also display population properties.     

Non-random clustering of stress-related genes during evolution of the S. cerevisiae genome

Background  

Coordinately regulated genes often physically cluster in eukaryotic genomes, for reasons that remain unclear.     

Asymmetric and non-uniform evolution of recently duplicated human genes

Background  

Gene duplications are a source of new genes and protein functions. The innovative role of duplication events makes families of paralogous genes an interesting target for studies in evolutionary biology. Here we study global trends in the evolution of human genes that resulted from recent duplications.     

Evolutionary origins of Brassicaceae specific genes in Arabidopsis thaliana

Background  

All sequenced genomes contain a proportion of lineage-specific genes, which exhibit no sequence similarity to any genes outside the lineage. Despite their prevalence, the origins and functions of most lineage-specific genes remain largely unknown. As more genomes are sequenced opportunities for understanding evolutionary origins and functions of lineage-specific genes are increasing.     

In search of suitable reference genes for gene expression studies of human renal cell carcinoma by real-time PCR

Background  

Housekeeping genes are commonly used as endogenous reference genes for the relative quantification of target genes in gene expression studies. No conclusive systematic study comparing the suitability of different candidate reference genes in clear cell renal cell carcinoma has been published to date. To remedy this situation, 10 housekeeping genes for normalizing purposes of RT-PCR measurements already recommended in various studies were examined with regard to their usefulness as reference genes.     

Identifying metabolic enzymes with multiple types of association evidence

Background  

Existing large-scale metabolic models of sequenced organisms commonly include enzymatic functions which can not be attributed to any gene in that organism. Existing computational strategies for identifying such missing genes rely primarily on sequence homology to known enzyme-encoding genes.     

Selecting normalization genes for small diagnostic microarrays

Background  

Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. Thus, applying standard microarray normalization strategies to diagnostic microarrays causes new normalization problems.     

Protein evolution of ANTP and PRD homeobox genes

Background  

Although homeobox genes have been the subject of many studies, little is known about the main amino acid changes that occurred early in the evolution of genes belonging to different classes.     

Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas

Background  

Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets.     

Transcriptomic response to differentiation induction

Background  

Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A common terminal data analysis step is to map pathways of potentially interrelated genes.     

Modified gateway system for double shRNA expression and Cre/lox based gene expression

Background  

The growing need for functional studies of genes has set the stage for the development of versatile tools for genetic manipulations.     

Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classification

Background  

Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of identification and annotation of bimodal genes in the human and mouse genomes. These switch-like genes consist of 15% of known human genes, and are enriched with genes coding for extracellular and membrane proteins. It is of interest to determine the prediction potential of bimodal genes for class discovery in large-scale datasets.     

Selection of reference genes for gene expression studies in human neutrophils by real-time PCR

Background  

Reference genes, which are often referred to housekeeping genes, are frequently used to normalize mRNA levels between different samples. However the expression level of these genes may vary among tissues or cells, and may change under certain circumstances. Thus the selection of reference gene(s) is critical for gene expression studies. For this purpose, 10 commonly used housekeeping genes were investigated in isolated human neutrophils.     

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks

Background  

We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the canonical variates, and we applied ridge penalization to the regression of pathway genes on canonical variates of the non-pathway genes, and the elastic net to the regression of non-pathway genes on the canonical variates of the pathway genes.