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Book ; Thesis: Test day models

Pool, Marco Henk

breeding value estimation based on individual test day records

2000

Title variant	Test-day models
Author's details	Marco Henk Pool
Keywords	Milchvieh ; Zuchtwertschätzung ; Regressionsschätzung
Subject	Regression estimate ; Regression estimation ; Erbwertermittlung ; Erbwertschätzung ; Zuchtwert ; Milchnutztiere
Language	English
Size	111 S. : Ill., graph. Darst.
Publishing country	Netherlands
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Wageningen, Univ., Diss., 2000
Note	Zsfassung in niederländ. Sprache
HBZ-ID	HT012893322
ISBN	90-5808-345-4 ; 978-90-5808-345-6
Database	Catalogue ZB MED Nutrition, Environment, Agriculture

In stock of ZB MED Bonn / Germany

Shelf mark	Loan status	Location
008/2243	available for loan (reading room)	Freihandmagazin (U1)

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Article ; Online: Biochemical pathways analysis of microarray results

Heuven Henri H / Pool Marco H / Coster Albart / Hulsegge Ina / te Pas Marinus FW / Janss Luc LG

BMC Developmental Biology, Vol 7, Iss 1, p

regulation of myogenesis in pigs

2007 Volume 66

Abstract: Abstract Background Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. Mammalian muscle formation has been previously ... ...

Abstract	Abstract Background Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. Mammalian muscle formation has been previously studied using microarray technology in pigs because these animals are an interesting animal model for muscle formation due to selection for increased muscle mass. Results indicated regulation of the expression of genes involved in proliferation and differentiation of myoblasts, and energy metabolism. The aim of the present study was to analyse microarrays studying myogenesis in pigs. It was necessary to develop methods to search biochemical pathways databases. Results PERL scripts were developed that used the names of the genes on the microarray to search databases. Synonyms of gene names were added to the list by searching the Gene Ontology database. The KEGG database was searched for pathway information using this updated gene list. The KEGG database returned 88 pathways. Most genes were found in a single pathway, but others were found in up to seven pathways. Combining the pathways and the microarray information 21 pathways showed sufficient information content for further analysis. These pathways were related to regulation of several steps in myogenesis and energy metabolism. Pathways regulating myoblast proliferation and muscle fibre formation were described. Furthermore, two networks of pathways describing the formation of the myoblast cytoskeleton and regulation of the energy metabolism during myogenesis were presented. Conclusion Combining microarray results and pathways information available through the internet provide biological insight in how the process of porcine myogenesis is regulated.
Keywords	Biology (General) ; QH301-705.5
Subject code	570
Language	English
Publishing date	2007-06-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Biochemical pathways analysis of microarray results: regulation of myogenesis in pigs.

Te Pas, Marinus F W / Hulsegge, Ina / Coster, Albart / Pool, Marco H / Heuven, Henri H / Janss, Luc L G

BMC developmental biology

2007 Volume 7, Page(s) 66

Abstract: Background: Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. Mammalian muscle formation has been previously studied ... ...

Abstract	Background: Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. Mammalian muscle formation has been previously studied using microarray technology in pigs because these animals are an interesting animal model for muscle formation due to selection for increased muscle mass. Results indicated regulation of the expression of genes involved in proliferation and differentiation of myoblasts, and energy metabolism. The aim of the present study was to analyse microarrays studying myogenesis in pigs. It was necessary to develop methods to search biochemical pathways databases. Results: PERL scripts were developed that used the names of the genes on the microarray to search databases. Synonyms of gene names were added to the list by searching the Gene Ontology database. The KEGG database was searched for pathway information using this updated gene list. The KEGG database returned 88 pathways. Most genes were found in a single pathway, but others were found in up to seven pathways. Combining the pathways and the microarray information 21 pathways showed sufficient information content for further analysis. These pathways were related to regulation of several steps in myogenesis and energy metabolism. Pathways regulating myoblast proliferation and muscle fibre formation were described. Furthermore, two networks of pathways describing the formation of the myoblast cytoskeleton and regulation of the energy metabolism during myogenesis were presented. Conclusion: Combining microarray results and pathways information available through the internet provide biological insight in how the process of porcine myogenesis is regulated.
MeSH term(s)	Animals ; Calcium/metabolism ; Databases, Genetic ; Female ; Gene Expression Profiling ; Gene Expression Regulation, Developmental ; Gestational Age ; Metabolic Networks and Pathways/physiology ; Muscle Development/physiology ; Oligonucleotide Array Sequence Analysis ; Pregnancy ; Receptors, Notch/genetics ; Receptors, Notch/metabolism ; Signal Transduction/physiology ; Swine ; Wnt Proteins/genetics ; Wnt Proteins/metabolism
Chemical Substances	Receptors, Notch ; Wnt Proteins ; Calcium (SY7Q814VUP)
Language	English
Publishing date	2007-06-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1471-213X
ISSN (online)	1471-213X
DOI	10.1186/1471-213X-7-66
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Transcriptome expression profiles in prenatal pigs in relation to myogenesis.

Te Pas, Marinus F W / De Wit, Agnes A W / Priem, Jan / Cagnazzo, Massimo / Davoli, Roberta / Russo, Vincenzo / Pool, Marco H

Journal of muscle research and cell motility

2005 Volume 26, Issue 2-3, Page(s) 157–165

Abstract: Myogenesis, the formation of muscle fibers, is a complex process. Pigs have been selected for efficient muscle growth for the past decades making them interesting to study myogenesis. We studied expression profiles of genes known to affect myogenesis, ... ...

Abstract	Myogenesis, the formation of muscle fibers, is a complex process. Pigs have been selected for efficient muscle growth for the past decades making them interesting to study myogenesis. We studied expression profiles of genes known to affect myogenesis, muscle structural proteins, and energy metabolism in prenatal pigs from 14 to 91 days of gestation. Primary and secondary muscle fiber formation takes place during days 30-60 and 54-90 of gestation, respectively. Differential expression and expression levels of the genes were studied using microarray technology. Gene activation and repression profiles were studied counting the number of spots with detectable signal. The number of spots for muscle tissue structural protein genes showing upregulated expression increased constantly from day 14 until day 91 of gestation indicating continued activation of genes during this period. The mRNA expression level of the genes showed a peak around day 35 of gestation. The expression levels of genes affecting myogenic differentiation (stimulating and inhibiting) showed a peak at day 35 of gestation. The number of spots for differentiation-stimulating genes showing differential expression reaches a first peak around day 35 of gestation and a nadir at day 49 of gestation while the number of spots for differentiation-inhibiting genes reaches a nadir at day 35 of gestation. Myogenic differentiation seems less a matter of the expression level of genes affecting differentiation, but depends on the balance between the number of significantly activated genes for stimulating and inhibiting differentiation. Genes stimulating myoblast proliferation showed a small peak expression prior to day 35 of gestation indicating myoblast proliferation before differentiation. The number of spots and the expression levels of genes for glycolysis and ATP-metabolism are at a nadir around days 35 and 49-63 of gestation suggesting that the energy metabolism is low during fusion of myoblasts into multinucleated muscle fibers.
MeSH term(s)	Animals ; Cell Differentiation ; Down-Regulation ; Gene Expression Regulation ; Microarray Analysis ; Muscle Development/genetics ; Muscle Proteins/metabolism ; Muscle, Skeletal/physiology ; Myogenic Regulatory Factors/physiology ; Oligonucleotide Array Sequence Analysis ; Polymerase Chain Reaction/methods ; RNA, Messenger/metabolism ; Reproducibility of Results ; Swine ; Transcription, Genetic ; Transcriptional Activation ; Up-Regulation
Chemical Substances	Muscle Proteins ; Myogenic Regulatory Factors ; RNA, Messenger
Language	English
Publishing date	2005
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	283053-x
ISSN	1573-2657 ; 0142-4319
ISSN (online)	1573-2657
ISSN	0142-4319
DOI	10.1007/s10974-005-7004-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analysis of a simulated microarray dataset

Genetics Selection Evolution, Vol 39, Iss 6, Pp 669-

Comparison of methods for data normalisation and detection of differential expression ( Open Access publication )

2007 Volume 683

Abstract: Abstract Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many ... ...

Abstract	Abstract Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set.
Keywords	gene expression ; two colour microarray ; simulation ; statistical analysis ; Genetics ; QH426-470 ; Biology (General) ; QH301-705.5 ; Science ; Q ; DOAJ:Genetics ; DOAJ:Biology ; DOAJ:Biology and Life Sciences
Subject code	310
Language	English
Publishing date	2007-11-01T00:00:00Z
Publisher	BioMed Central
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Analysis of a simulated microarray dataset: comparison of methods for data normalisation and detection of differential expression (open access publication).

Genetics, selection, evolution : GSE

2007 Volume 39, Issue 6, Page(s) 669–683

Abstract: Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been ... ...

Abstract	Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set.
MeSH term(s)	Animals ; Animals, Domestic/genetics ; Computer Simulation ; Data Interpretation, Statistical ; Databases, Genetic ; Europe ; Gene Expression Profiling/statistics & numerical data ; Oligonucleotide Array Sequence Analysis/statistics & numerical data ; Software
Language	English
Publishing date	2007-12-06
Publishing country	France
Document type	Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1005838-2
ISSN	0999-193X
ISSN	0999-193X
DOI	10.1186/1297-9686-39-6-669
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The EADGENE Microarray Data Analysis Workshop ( Open Access publication )

Jiménez-Marín Ángeles / Waddington David / Mouzaki Daphne / Jensen Kirsty / Seyfert Hans-Martin / Brunner Ronald M / Stella Alessandra / Malinverni Roberto / Baron Michael D / San Cristobal Magali / Cao Kim-Anh / Delmas Céline / Marot Guillemette / Sørensen Peter / Jiang Li / Hornshøj Henrik / Hedegaard Jakob / Buitenhuis Bart / Pool Marco H /

Hulsegge Ina / Channing Caroline / Watson Michael / Lund Mogens / Jaffrézic Florence / de Koning Dirk-Jan / Pérez-Alegre Mónica / Pérez-Reinado Eva / Closset Rodrigue / Detilleux Johanne C / Dovč Peter / Lavrič Miha / Nie Haisheng / Janss Luc

Genetics Selection Evolution, Vol 39, Iss 6, Pp 621-

2007 Volume 631

Abstract: Abstract Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, ...

Abstract	Abstract Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.
Keywords	gene expression ; two colour microarray ; statistical analysis ; Genetics ; QH426-470 ; Biology (General) ; QH301-705.5 ; Science ; Q ; DOAJ:Genetics ; DOAJ:Biology ; DOAJ:Biology and Life Sciences
Subject code	310
Language	English
Publishing date	2007-11-01T00:00:00Z
Publisher	BioMed Central
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Analysis of the real EADGENE data set

Schuberth Hans-Joachim / van Schothorst Evert M / Lund Mogens / San Cristobal Magali / Robert-Granié Christèle / Pool Marco H / Petzl Wolfram / Nie Haisheng / Cao Kim-Anh / de Koning Dirk-Jan / Jiang Li / Jensen Kirsty / Hulsegge Ina / Jaffrézic Florence / Hornshøj Henrik / Hedegaard Jakob / Glass Liz / Duval Mylène / Delmas Céline /

Déjean Sébastien / Closset Rodrigue / Buitenhuis Bart / Bonnet Agnès / Sørensen Peter / Seyfert Hans-Martin / Tosser-Klopp Gwenola / Waddington David / Watson Michael / Yang Wei / Zerbe Holm

Genetics Selection Evolution, Vol 39, Iss 6, Pp 651-

Multivariate approaches and post analysis ( Open Access publication )

2007 Volume 668

Abstract: Abstract The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at ... ...

Abstract	Abstract The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent ( E. coli or S. aureus ). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus . The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.
Keywords	bovine annotation ; bovine microarray ; gene set analysis ; mastitis ; multivariate approaches ; Genetics ; QH426-470 ; Biology (General) ; QH301-705.5 ; Science ; Q ; DOAJ:Genetics ; DOAJ:Biology ; DOAJ:Biology and Life Sciences
Subject code	570
Language	English
Publishing date	2007-11-01T00:00:00Z
Publisher	BioMed Central
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Analysis of the real EADGENE data set: multivariate approaches and post analysis (open access publication).

Sørensen, Peter / Bonnet, Agnès / Buitenhuis, Bart / Closset, Rodrigue / Déjean, Sébastien / Delmas, Céline / Duval, Mylène / Glass, Liz / Hedegaard, Jakob / Hornshøj, Henrik / Hulsegge, Ina / Jaffrézic, Florence / Jensen, Kirsty / Jiang, Li / de Koning, Dirk-Jan / Lê Cao, Kim-Anh / Nie, Haisheng / Petzl, Wolfram / Pool, Marco H /

Robert-Granié, Christèle / San Cristobal, Magali / Lund, Mogens Sandø / van Schothorst, Evert M / Schuberth, Hans-Joachim / Seyfert, Hans-Martin / Tosser-Klopp, Gwenola / Waddington, David / Watson, Michael / Yang, Wei / Zerbe, Holm

Genetics, selection, evolution : GSE

2007 Volume 39, Issue 6, Page(s) 651–668

Abstract: The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. ... ...

Abstract	The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent (E. coli or S. aureus). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus. The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.
MeSH term(s)	Animals ; Animals, Domestic/genetics ; Cattle/genetics ; Data Interpretation, Statistical ; Databases, Genetic ; Escherichia coli Infections/genetics ; Escherichia coli Infections/veterinary ; Europe ; Female ; Gene Expression Profiling/statistics & numerical data ; Host-Pathogen Interactions/genetics ; Mastitis, Bovine/genetics ; Multivariate Analysis ; Oligonucleotide Array Sequence Analysis/statistics & numerical data ; Staphylococcal Infections/genetics ; Staphylococcal Infections/veterinary
Language	English
Publishing date	2007-12-06
Publishing country	France
Document type	Comparative Study ; Congress ; Research Support, Non-U.S. Gov't
ZDB-ID	1005838-2
ISSN	0999-193X
ISSN	0999-193X
DOI	10.1186/1297-9686-39-6-651
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: The EADGENE Microarray Data Analysis Workshop (open access publication).

de Koning, Dirk-Jan / Jaffrézic, Florence / Lund, Mogens Sandø / Watson, Michael / Channing, Caroline / Hulsegge, Ina / Pool, Marco H / Buitenhuis, Bart / Hedegaard, Jakob / Hornshøj, Henrik / Jiang, Li / Sørensen, Peter / Marot, Guillemette / Delmas, Céline / Lê Cao, Kim-Anh / San Cristobal, Magali / Baron, Michael D / Malinverni, Roberto / Stella, Alessandra /

Brunner, Ronald M / Seyfert, Hans-Martin / Jensen, Kirsty / Mouzaki, Daphne / Waddington, David / Jiménez-Marín, Angeles / Pérez-Alegre, Mónica / Pérez-Reinado, Eva / Closset, Rodrigue / Detilleux, Johanne C / Dovc, Peter / Lavric, Miha / Nie, Haisheng / Janss, Luc

Genetics, selection, evolution : GSE

2007 Volume 39, Issue 6, Page(s) 621–631

Abstract: Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 ... ...

Abstract	Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.
MeSH term(s)	Animals ; Animals, Domestic/genetics ; Cattle ; Computer Simulation ; Data Interpretation, Statistical ; Escherichia coli Infections/genetics ; Escherichia coli Infections/veterinary ; Europe ; Female ; Gene Expression Profiling/standards ; Gene Expression Profiling/statistics & numerical data ; Host-Pathogen Interactions/genetics ; Mastitis, Bovine/genetics ; Oligonucleotide Array Sequence Analysis/standards ; Oligonucleotide Array Sequence Analysis/statistics & numerical data ; Quality Control ; Staphylococcal Infections/genetics ; Staphylococcal Infections/veterinary
Language	English
Publishing date	2007-12-06
Publishing country	France
Document type	Congress ; Research Support, Non-U.S. Gov't
ZDB-ID	1005838-2
ISSN	0999-193X
ISSN	0999-193X
DOI	10.1186/1297-9686-39-6-621
Database	MEDical Literature Analysis and Retrieval System OnLINE

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