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Full-Text Articles in Life Sciences

Alternative Probeset Definitions For Combining Microarray Data Across Studies Using Different Versions Of Affymetrix Oligonucleotide Arrays, Jeffrey S. Morris, Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, Li Zhang Dec 2006

Alternative Probeset Definitions For Combining Microarray Data Across Studies Using Different Versions Of Affymetrix Oligonucleotide Arrays, Jeffrey S. Morris, Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, Li Zhang

Jeffrey S. Morris

Many published microarray studies have small to moderate sample sizes, and thus have low statistical power to detect significant relationships between gene expression levels and outcomes of interest. By pooling data across multiple studies, however, we can gain power, enabling us to detect new relationships. This type of pooling is complicated by the fact that gene expression measurements from different microarray platforms are not directly comparable. In this chapter, we discuss two methods for combining information across different versions of Affymetrix oligonucleotide arrays. Each involves a new approach for combining probes on the array into probesets. The first approach involves ...


Genomeblast: A Web Tool For Small Genome Comparison, Guoqing Lu, Liying Jiang, Resa M. K. Helikar, Thaine W. Rowley, Luwen Zhang, Xianfeng Chen, Etsuko N. Moriyama Dec 2006

Genomeblast: A Web Tool For Small Genome Comparison, Guoqing Lu, Liying Jiang, Resa M. K. Helikar, Thaine W. Rowley, Luwen Zhang, Xianfeng Chen, Etsuko N. Moriyama

Biology Faculty Publications

Background: Comparative genomics has become an essential approach for identifying homologous gene candidates and their functions, and for studying genome evolution. There are many tools available for genome comparisons. Unfortunately, most of them are not applicable for the identification of unique genes and the inference of phylogenetic relationships in a given set of genomes.

Results: GenomeBlast is a Web tool developed for comparative analysis of multiple small genomes. A new parameter called "coverage" was introduced and used along with sequence identity to evaluate global similarity between genes. With GenomeBlast, the following results can be obtained: (1) unique genes in each ...


Some Statistical Issues In Microarray Gene Expression Data, Matthew S. Mayo, Byron J. Gajewski, Jeffrey S. Morris Jun 2006

Some Statistical Issues In Microarray Gene Expression Data, Matthew S. Mayo, Byron J. Gajewski, Jeffrey S. Morris

Jeffrey S. Morris

In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three contexts: class comparison, class prediction and class discovery. We also review the methods used in two studies that are using microarray gene expression to assess the effect of exposure to radiofrequency (RF) fields on gene expression. Our intent is to provide a guide for radiation researchers when conducting studies involving microarray gene expression ...


Shelling Out For Genomics, Timothy S. Mcclintock, Charles D. Derby Apr 2006

Shelling Out For Genomics, Timothy S. Mcclintock, Charles D. Derby

Physiology Faculty Publications

A report on the symposium 'Genomic and Proteomic Approaches to Crustacean Biology' held as part of the Society for Integrative and Comparative Biology 2006 Annual Meeting, Orlando, USA, 4-8 January 2006.


Shrinkage Estimation For Sage Data Using A Mixture Dirichlet Prior, Jeffrey S. Morris, Keith A. Baggerly, Kevin R. Coombes Mar 2006

Shrinkage Estimation For Sage Data Using A Mixture Dirichlet Prior, Jeffrey S. Morris, Keith A. Baggerly, Kevin R. Coombes

Jeffrey S. Morris

Serial Analysis of Gene Expression (SAGE) is a technique for estimating the gene expression profile of a biological sample. Any efficient inference in SAGE must be based upon efficient estimates of these gene expression profiles, which consist of the estimated relative abundances for each mRNA species present in the sample. The data from SAGE experiments are counts for each observed mRNA species, and can be modeled using a multinomial distribution with two characteristics: skewness in the distribution of relative abundances and small sample size relative to the dimension. As a result of these characteristics, a given SAGE sample will fail ...


An Introduction To High-Throughput Bioinformatics Data, Keith A. Baggerly, Kevin R. Coombes, Jeffrey S. Morris Mar 2006

An Introduction To High-Throughput Bioinformatics Data, Keith A. Baggerly, Kevin R. Coombes, Jeffrey S. Morris

Jeffrey S. Morris

High throughput biological assays supply thousands of measurements per sample, and the sheer amount of related data increases the need for better models to enhance inference. Such models, however, are more effective if they take into account the idiosyncracies associated with the specific methods of measurement: where the numbers come from. We illustrate this point by describing three different measurement platforms: microarrays, serial analysis of gene expression (SAGE), and proteomic mass spectrometry.


Bayesian Mixture Models For Gene Expression And Protein Profiles, Michele Guindani, Kim-Anh Do, Peter Mueller, Jeffrey S. Morris Mar 2006

Bayesian Mixture Models For Gene Expression And Protein Profiles, Michele Guindani, Kim-Anh Do, Peter Mueller, Jeffrey S. Morris

Jeffrey S. Morris

We review the use of semi-parametric mixture models for Bayesian inference in high throughput genomic data. We discuss three specific approaches for microarray data, for protein mass spectrometry experiments, and for SAGE data. For the microarray data and the protein mass spectrometry we assume group comparison experiments, i.e., experiments that seek to identify genes and proteins that are differentially expressed across two biologic conditions of interest. For the SAGE data example we consider inference for a single biologic sample.


Adaptive Evolution Of Chloroplast Genome Structure Inferred Using A Parametric Bootstrap Approach, Liying Cui, Jim Leebens-Mack, Li-San Wang, Jijun Tang, Linda Rymarquis, David B. Stern, Claude W. Depamphilis Feb 2006

Adaptive Evolution Of Chloroplast Genome Structure Inferred Using A Parametric Bootstrap Approach, Liying Cui, Jim Leebens-Mack, Li-San Wang, Jijun Tang, Linda Rymarquis, David B. Stern, Claude W. Depamphilis

Faculty Publications

Background
Genome rearrangements influence gene order and configuration of gene clusters in all genomes. Most land plant chloroplast DNAs (cpDNAs) share a highly conserved gene content and with notable exceptions, a largely co-linear gene order. Conserved gene orders may reflect a slow intrinsic rate of neutral chromosomal rearrangements, or selective constraint. It is unknown to what extent observed changes in gene order are random or adaptive. We investigate the influence of natural selection on gene order in association with increased rate of chromosomal rearrangement. We use a novel parametric bootstrap approach to test if directional selection is responsible for the ...


Evidence From Mitochondrial Genomics On Interordinal Relationships In Insects, Stephen L. Cameron, Andrew T. Beckenbach, Mark P. Dowton, Michael F. Whiting Jan 2006

Evidence From Mitochondrial Genomics On Interordinal Relationships In Insects, Stephen L. Cameron, Andrew T. Beckenbach, Mark P. Dowton, Michael F. Whiting

Faculty of Science - Papers (Archive)

No abstract provided.


Phylogeny, Genome Size, And Chromosome Evolution Of Asparagales, J. Chris Pires, Ivan J. Maureira, Thomas J. Givnish, Kenneth J. Systma, Ole Seberg, Gitte Peterson, Jerrold I. Davis, Dennis W. Stevenson, Paula J. Rudall, Michael F. Fay, Mark W. Chase Jan 2006

Phylogeny, Genome Size, And Chromosome Evolution Of Asparagales, J. Chris Pires, Ivan J. Maureira, Thomas J. Givnish, Kenneth J. Systma, Ole Seberg, Gitte Peterson, Jerrold I. Davis, Dennis W. Stevenson, Paula J. Rudall, Michael F. Fay, Mark W. Chase

Aliso: A Journal of Systematic and Evolutionary Botany

Asparagales are a diverse monophyletic order that has numerous species (ca. 50% of monocots) including important crop plants such as Allium, Asparagus, and Vanilla, and a host of ornamentals such as irises, hyacinths, and orchids. Historically, Asparagales have been of interest partly because of their fascinating chromosomal evolution. We examine the evolutionary dynamics of Asparagales genomes in an updated phylogenetic framework that combines analyses of seven gene regions (atp1, atpB, matK, ndhF, rbcL, trnL intron, and trnL-F intergenic spacer) for 79 taxa of Asparagales and outgroups. Asparagales genomes are evolutionarily labile for many ...