<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hoogerwerf, W. A.</style></author><author><style face="normal" font="default" size="100%">Sinha, M.</style></author><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Luxon, B. A.</style></author><author><style face="normal" font="default" size="100%">Shahinian, V. B.</style></author><author><style face="normal" font="default" size="100%">Cornelissen, G.</style></author><author><style face="normal" font="default" size="100%">Halberg, F.</style></author><author><style face="normal" font="default" size="100%">Bostwick, J.</style></author><author><style face="normal" font="default" size="100%">Timm, J.</style></author><author><style face="normal" font="default" size="100%">Cassone, V. M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcriptional profiling of mRNA expression in the mouse distal colon</style></title><secondary-title><style face="normal" font="default" size="100%">Gastroenterology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals Blotting</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Inbred C57BL Microarray Analysis Proteins/*genetics/metabolism RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Messenger/biosynthesis/*genetics Reverse Transcriptase Polymerase Chain Reaction *Transcription</style></keyword><keyword><style  face="normal" font="default" size="100%">Western Cell Proliferation Circadian Rhythm/*genetics Colon/cytology/*metabolism Male Mice Mice</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=18848557</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">135</style></volume><pages><style face="normal" font="default" size="100%">2019-29</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND &amp; AIMS: Intestinal epithelial cells and the myenteric plexus of the mouse gastrointestinal tract contain a circadian clock-based intrinsic time-keeping system. Because disruption of the biological clock has been associated with increased susceptibility to colon cancer and gastrointestinal symptoms, we aimed to identify rhythmically expressed genes in the mouse distal colon. METHODS: Microarray analysis was used to identify genes that were rhythmically expressed over a 24-hour light/dark cycle. The transcripts were then classified according to expression pattern, function, and association with physiologic and pathophysiologic processes of the colon. RESULTS: A circadian gene expression pattern was detected in approximately 3.7% of distal colonic genes. A large percentage of these genes were involved in cell signaling, differentiation, and proliferation and cell death. Of all the rhythmically expressed genes in the mouse colon, approximately 7% (64/906) have been associated with colorectal cancer formation (eg, B-cell leukemia/lymphoma-2 [Bcl2]) and 1.8% (18/906) with various colonic functions such as motility and secretion (eg, vasoactive intestinal polypeptide, cystic fibrosis transmembrane conductance regulator). CONCLUSIONS: A subset of genes in the murine colon follows a rhythmic expression pattern. These findings may have significant implications for colonic physiology and pathophysiology.</style></abstract><notes><style face="normal" font="default" size="100%">Hoogerwerf, Willemijntje A Sinha, Mala Conesa, Ana Luxon, Bruce A Shahinian, Vahakn B Cornelissen, Germaine Halberg, Franz Bostwick, Jonathon Timm, John Cassone, Vincent M R21 DK074477-01A1/DK/NIDDK NIH HHS/United States Comparative Study Research Support, N.I.H., Extramural United States Gastroenterology Gastroenterology. 2008 Dec;135(6):2019-29. Epub 2008 Sep 3.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nueda, M. J.</style></author><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Westerhuis, J. A.</style></author><author><style face="normal" font="default" size="100%">Hoefsloot, H. C.</style></author><author><style face="normal" font="default" size="100%">Smilde, A. K.</style></author><author><style face="normal" font="default" size="100%">Talon, M.</style></author><author><style face="normal" font="default" size="100%">Ferrer, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms *Analysis of Variance Computational Biology/*methods Computer Simulation Data Interpretation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical Gene Expression Profiling/*methods Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical Oligonucleotide Array Sequence Analysis/*methods Principal Component Analysis Time Factors Transcription</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17519250</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">14</style></number><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">1792-800</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MOTIVATION: Designed microarray experiments are used to investigate the effects that controlled experimental factors have on gene expression and learn about the transcriptional responses associated with external variables. In these datasets, signals of interest coexist with varying sources of unwanted noise in a framework of (co)relation among the measured variables and with the different levels of the studied factors. Discovering experimentally relevant transcriptional changes require methodologies that take all these elements into account. RESULTS: In this work, we develop the application of the Analysis of variance-simultaneous component analysis (ANOVA-SCA) Smilde et al. Bioinformatics, (2005) to the analysis of multiple series time course microarray data as an example of multifactorial gene expression profiling experiments. We denoted this implementation as ASCA-genes. We show how the combination of ANOVA-modeling and a dimension reduction technique is effective in extracting targeted signals from data by-passing structural noise. The methodology is valuable for identifying main and secondary responses associated with the experimental factors and spotting relevant experimental conditions. We additionally propose a novel approach for gene selection in the context of the relation of individual transcriptional patterns to global gene expression signals. We demonstrate the methodology on both real and synthetic datasets. AVAILABILITY: ASCA-genes has been implemented in the statistical language R and is available at http://www.ivia.es/centrodegenomica/bioinformatics.htm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.</style></abstract><notes><style face="normal" font="default" size="100%">Nueda, Maria Jose Conesa, Ana Westerhuis, Johan A Hoefsloot, Huub C J Smilde, Age K Talon, Manuel Ferrer, Alberto Research Support, Non-U.S. Gov’t England Bioinformatics (Oxford, England) Bioinformatics. 2007 Jul 15;23(14):1792-800. Epub 2007 May 22.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gandia, M.</style></author><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Ancillo, G.</style></author><author><style face="normal" font="default" size="100%">J. Gadea</style></author><author><style face="normal" font="default" size="100%">J. Forment</style></author><author><style face="normal" font="default" size="100%">Pallas, V.</style></author><author><style face="normal" font="default" size="100%">Flores, R.</style></author><author><style face="normal" font="default" size="100%">Duran-Vila, N.</style></author><author><style face="normal" font="default" size="100%">Moreno, P.</style></author><author><style face="normal" font="default" size="100%">Guerri, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcriptional response of Citrus aurantifolia to infection by Citrus tristeza virus</style></title><secondary-title><style face="normal" font="default" size="100%">Virology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Citrus/*genetics/physiology/virology Closterovirus/genetics/*physiology Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Oligonucleotide Array Sequence Analysis Reverse Transcriptase Polymerase Chain Reaction *Transcription</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17617431</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">367</style></volume><pages><style face="normal" font="default" size="100%">298-306</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Changes in gene expression of Mexican lime plants in response to infection with a severe (T305) or a mild (T385) isolate of Citrus tristeza virus (CTV) were analyzed using a cDNA microarray containing 12,672 probes to 6875 different citrus genes. Statistically significant (P&lt;0.01) expression changes of 334 genes were detected in response to infection with isolate T305, whereas infection with T385 induced no significant change. Induced genes included 145 without significant similarity with known sequences and 189 that were classified in seven functional categories. Genes related with response to stress and defense were the main category and included 28% of the genes induced. Selected transcription changes detected by microarray analysis were confirmed by quantitative real-time RT-PCR. Changes detected in the transcriptome upon infecting lime with T305 may be associated either with symptom expression, with a strain-specific defense mechanism, or with a general response to stress.</style></abstract><notes><style face="normal" font="default" size="100%">Gandia, Monica Conesa, Ana Ancillo, Gema Gadea, Jose Forment, Javier Pallas, Vicente Flores, Ricardo Duran-Vila, Nuria Moreno, Pedro Guerri, Jose Research Support, Non-U.S. Gov’t United States Virology Virology. 2007 Oct 25;367(2):298-306. Epub 2007 Jul 9.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Jeenes, D.</style></author><author><style face="normal" font="default" size="100%">Archer, D. B.</style></author><author><style face="normal" font="default" size="100%">van den Hondel, C. A.</style></author><author><style face="normal" font="default" size="100%">Punt, P. J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Calnexin overexpression increases manganese peroxidase production in Aspergillus niger</style></title><secondary-title><style face="normal" font="default" size="100%">Appl Environ Microbiol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aspergillus niger/*enzymology/genetics Calcium-Binding Proteins/*metabolism Calnexin Culture Media *Fungal Proteins HSP70 Heat-Shock Proteins/metabolism Heme/metabolism Peroxidases/*biosynthesis/genetics Phanerochaete/enzymology/genetics Transformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=11823227</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">68</style></volume><pages><style face="normal" font="default" size="100%">846-51</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Heme-containing peroxidases from white rot basidiomycetes, in contrast to most proteins of fungal origin, are poorly produced in industrial filamentous fungal strains. Factors limiting peroxidase production are believed to operate at the posttranslational level. In particular, insufficient availability of the prosthetic group which is required for peroxidase biosynthesis has been proposed to be an important bottleneck. In this work, we analyzed the role of two components of the secretion pathway, the chaperones calnexin and binding protein (BiP), in the production of a fungal peroxidase. Expression of the Phanerochaete chrysosporium manganese peroxidase (MnP) in Aspergillus niger resulted in an increase in the expression level of the clxA and bipA genes. In a heme-supplemented medium, where MnP was shown to be overproduced to higher levels, induction of clxA and bipA was also higher. Overexpression of these two chaperones in an MnP-producing strain was analyzed for its effect on MnP production. Whereas bipA overexpression seriously reduced MnP production, overexpression of calnexin resulted in a four- to fivefold increase in the extracellular MnP levels. However, when additional heme was provided in the culture medium, calnexin overexpression had no synergistic effect on MnP production. The possible function of these two chaperones in MnP maturation and production is discussed.</style></abstract><notes><style face="normal" font="default" size="100%">Conesa, Ana Jeenes, David Archer, David B van den Hondel, Cees A M J J Punt, Peter J United States Applied and environmental microbiology Appl Environ Microbiol. 2002 Feb;68(2):846-51.</style></notes></record></records></xml>