Biomedical subjects

Philip Zimmermann

Publications and source records attributed to Philip Zimmermann.

11 recordsLinked to original sources

PubMed2006

Web-based analysis of the mouse transcriptome using Genevestigator.

BACKGROUND: Gene function analysis often requires a complex and laborious sequence of laboratory and computer-based experiments. Choosing an effective experimental design generally results from hypotheses derived from prior knowledge or experimentation. Knowledge obtained from meta-analyzing compendia of expression data with annotation libraries can provide significant clues in understanding gene and network function, resulting in better hypotheses that can be tested in the laboratory. DESCRIPTION: Genevestigator is a microarray database and analysis system allowing context-driven queries. Simple but powerful tools allow biologists with little computational background to retrieve information about when, where and how genes are expressed. We manually curated and quality-controlled 3110 mouse Affymetrix arrays from public repositories. Data queries can be run against an annotation library comprising 160 anatomy categories, 12 developmental stage groups, 80 stimuli, and 182 genetic backgrounds or modifications. The quality of results obtained through Genevestigator is illustrated by a number of biological scenarios that are substantiated by other types of experimentation in the literature. CONCLUSION: The Genevestigator-Mouse database effectively provides biologically meaningful results and can be accessed at https://www.genevestigator.ethz.ch.

Animals↗

PubMed2006

BicAT: a biclustering analysis toolbox.

SUMMARY: Besides classical clustering methods such as hierarchical clustering, in recent years biclustering has become a popular approach to analyze biological data sets, e.g. gene expression data. The Biclustering Analysis Toolbox (BicAT) is a software platform for clustering-based data analysis that integrates various biclustering and clustering techniques in terms of a common graphical user interface. Furthermore, BicAT provides different facilities for data preparation, inspection and postprocessing such as discretization, filtering of biclusters according to specific criteria or gene pair analysis for constructing gene interconnection graphs. The possibility to use different biclustering algorithms inside a single graphical tool allows the user to compare clustering results and choose the algorithm that best fits a specific biological scenario. The toolbox is described in the context of gene expression analysis, but is also applicable to other types of data, e.g. data from proteomics or synthetic lethal experiments. AVAILABILITY: The BicAT toolbox is freely available at http://www.tik.ee.ethz.ch/sop/bicat and runs on all operating systems. The Java source code of the program and a developer's guide is provided on the website as well. Therefore, users may modify the program and add further algorithms or extensions.

Algorithms↗

PubMed2006

A systematic comparison and evaluation of biclustering methods for gene expression data.

MOTIVATION: In recent years, there have been various efforts to overcome the limitations of standard clustering approaches for the analysis of gene expression data by grouping genes and samples simultaneously. The underlying concept, which is often referred to as biclustering, allows to identify sets of genes sharing compatible expression patterns across subsets of samples, and its usefulness has been demonstrated for different organisms and datasets. Several biclustering methods have been proposed in the literature; however, it is not clear how the different techniques compare with each other with respect to the biological relevance of the clusters as well as with other characteristics such as robustness and sensitivity to noise. Accordingly, no guidelines concerning the choice of the biclustering method are currently available. RESULTS: First, this paper provides a methodology for comparing and validating biclustering methods that includes a simple binary reference model. Although this model captures the essential features of most biclustering approaches, it is still simple enough to exactly determine all optimal groupings; to this end, we propose a fast divide-and-conquer algorithm (Bimax). Second, we evaluate the performance of five salient biclustering algorithms together with the reference model and a hierarchical clustering method on various synthetic and real datasets for Saccharomyces cerevisiae and Arabidopsis thaliana. The comparison reveals that (1) biclustering in general has advantages over a conventional hierarchical clustering approach, (2) there are considerable performance differences between the tested methods and (3) already the simple reference model delivers relevant patterns within all considered settings.

Algorithms↗

PubMed2006

MIAME/Plant - adding value to plant microarrray experiments.

Appropriate biological interpretation of microarray data calls for relevant experimental annotation. The widely accepted MIAME guidelines provide a generic, organism-independant standard for minimal information about microarray experiments. In its overall structure, MIAME is very general and specifications cover mostly technical aspects, while relevant organism-specific information useful to understand the underlying experiments is largely missing. If plant biologists want to use results from published microarray experiments, they need detailed information about biological aspects, such as growth conditions, harvesting time or harvested organ(s). Here, we propose MIAME/Plant, a standard describing which biological details to be captured for describing microarray experiments involving plants. We expect that a more detailed and more systematic annotation of microarray experiments will greatly increase the use of transcriptome data sets for the scientific community. The power and value of systematic annotation of microarray data is convincingly demonstrated by data warehouses such as Genevestigator(R) or NASCArrays, and better experimental annotation will make these applications even more powerful.

Editorial↗

PubMed2005

Genome-wide analysis of hydrogen peroxide-regulated gene expression in Arabidopsis reveals a high light-induced transcriptional cluster involved in anthocyanin biosynthesis.

In plants, reactive oxygen species and, more particularly, hydrogen peroxide (H(2)O(2)) play a dual role as toxic by-products of normal cell metabolism and as regulatory molecules in stress perception and signal transduction. Peroxisomal catalases are an important sink for photorespiratory H(2)O(2). Using ATH1 Affymetrix microarrays, expression profiles were compared between control and catalase-deficient Arabidopsis (Arabidopsis thaliana) plants. Reduced catalase levels already provoked differences in nuclear gene expression under ambient growth conditions, and these effects were amplified by high light exposure in a sun simulator for 3 and 8 h. This genome-wide expression analysis allowed us to reveal the expression characteristics of complete pathways and functional categories during H(2)O(2) stress. In total, 349 transcripts were significantly up-regulated by high light in catalase-deficient plants and 88 were down-regulated. From this data set, H(2)O(2) was inferred to play a key role in the transcriptional up-regulation of small heat shock proteins during high light stress. In addition, several transcription factors and candidate regulatory genes involved in H(2)O(2) transcriptional gene networks were identified. Comparisons with other publicly available transcriptome data sets of abiotically stressed Arabidopsis revealed an important intersection with H(2)O(2)-deregulated genes, positioning elevated H(2)O(2) levels as an important signal within abiotic stress-induced gene expression. Finally, analysis of transcriptional changes in a combination of a genetic (catalase deficiency) and an environmental (high light) perturbation identified a transcriptional cluster that was strongly and rapidly induced by high light in control plants, but impaired in catalase-deficient plants. This cluster comprises the complete known anthocyanin regulatory and biosynthetic pathway, together with genes encoding unknown proteins.

Anthocyanins↗

PubMed2005

Gene-expression analysis and network discovery using Genevestigator.

The Genevestigator software suite belongs to a new generation of web-based tools that provide categorized quantitative information about elements (genes or annotations) contained in large microarray databases. The first version of Genevestigator, in use since 2004, has now been updated to enable faster, more powerful and more diverse types of queries for gene-function analysis and network discovery.

Databases, Genetic↗

PubMed2004

Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana.

We present a novel graphical Gaussian modeling approach for reverse engineering of genetic regulatory networks with many genes and few observations. When applying our approach to infer a gene network for isoprenoid biosynthesis in Arabidopsis thaliana, we detect modules of closely connected genes and candidate genes for possible cross-talk between the isoprenoid pathways. Genes of downstream pathways also fit well into the network. We evaluate our approach in a simulation study and using the yeast galactose network.

Arabidopsis↗

PubMed2004

GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox.

High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch.

Arabidopsis↗

PubMed2004

Expression analysis suggests novel roles for the plastidic phosphate transporter Pht2;1 in auto- and heterotrophic tissues in potato and Arabidopsis.

A cDNA encoding Pht2;1 from potato, a new member of the plant Pht2 gene family of low-affinity orthophosphate (Pi) transporters, was isolated. The expression pattern of the corresponding gene as well as its ortholog from Arabidopsis was analyzed and the encoded proteins were localized in the two plants. Pht2;1 expression is strongly upregulated by light in potato and Arabidopsis leaf tissue. RNA gel blot analysis, reverse transcription-polymerase chain reaction (RT-PCR), promoter/GUS, and protein/green fluorescent protein (GFP) fusion studies, respectively, indicate that the gene is expressed in both auto- and heterotrophic tissues and its encoded protein is localized to the plastids. The similar patterns of Pht2;1 gene regulation in potato and Arabidopsis prompted us to screen publicly available gene expression data from 228 Arabidopsis oligonucleotide microarrays covering 83 different experimental conditions. Modulation of Pht2;1 transcript levels was overall moderate, except for a limited number of experimental conditions where Pht2;1 mRNA concentrations varied between 2- and 3.7-fold. Overall, these analyses suggest involvement of the Pht2;1 protein in cell wall metabolism in young, rapidly growing tissues, independent of other Pi transporters such as the high-affinity Solanum tuberosum Pi transporter 1 (StPT1). Cluster analysis allowed identification of colinear or antiparallel expression profiles of a small set of genes involved in post-translational regulation, and photosynthetic carbon metabolism. These data give clues about the possible biological function of Pht2;1 and shed light on the complex web of interactions in which Pht2;1 could play a role.

Amino Acid Sequence↗

PubMed2003

Engineering the root-soil interface via targeted expression of a synthetic phytase gene in trichoblasts.

For biochemical modification of the root-soil interface, the engineered secretion of stable enzymes from trichoblasts (= root hair bearing rhizodermal cells) is proposed. As a reporter activity, we chose to express a synthetic gene encoding a secretory phytase (PHY) directed by a trichoblast-specific promoter in root hair cells of the crop plant potato. Transgenic plants produced and secreted phytase in sufficient amounts to release phosphate from phytate in liquid medium. When grown in an unsterile substrate containing phytate, transgenic plants accumulated 40% more P in leaves than wild-type plants. The improved P nutrition driven by trichoblast-targeted expression and subsequent secretion of PHY illustrates the potential of using trichoblast-targeted expression of suitable enzymes for future applications in plant nutrition, phytoremediation and molecular farming.

Journal Article↗

PubMed2002

The expression of an extensin-like protein correlates with cellular tip growth in tomato.

Extensins are abundant proteins presumed to determine physical characteristics of the plant cell wall. We have cloned a cDNA encoding LeExt1 from a tomato (Lycopersicon esculentum Mill.) root hair cDNA library. The deduced sequence of the LeExt1 polypeptide defined a novel type of extensin-like proteins in tomato. Patterns of mRNA distribution indicated that expression of the LeExt1 gene was initiated in the root hair differentiation zone of the tomato rhizodermis. Cloning of the corresponding promoter and fusion to the -glucuronidase (GUS) reporter gene allowed detailed examination of LeExt1 expression in transgenic tomato plants. Evidence is presented for a direct correlation between LeExt1 expression and cellular tip growth. LeExt1/GUS expression was detectable in trichoblasts (=root hair-bearing cells), but not in atrichoblasts of the tomato rhizodermis. Both hair formation and LeExt1 expression was inducible by the plant hormone ethylene. Comparative analysis of the LeExt1/GUS expression was performed in transgenic tomato, potato (Solanum tuberosum), tobacco (Nicotiana tabacum), and Arabidopsis plants. In the apical/basal dimension, GUS staining was absent from the root cap and undifferentiated cells at the root tip in all species investigated. It was induced at the distal end of the differentiation zone and remained high proximally to the root/hypocotyl boundary. In the radial dimension, GUS expression was root hair specific in the solanaceous species. Whereas LeExt1 mRNA was exclusively detectable in the rhizodermis, root hair-specific expression correlated with GUS expression in germinating pollen tubes. This is correlative evidence for a role of LeExt1 in root hair tip growth [corrected].

Amino Acid Sequence↗