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GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox

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TLDR
Genevestigator as mentioned in this paper is a web-browser interface for gene expression analysis using Affymetrix GeneChip data, which allows users to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs.
Abstract
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.

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Unique, Shared, and Redundant Roles for the Arabidopsis SWI/SNF Chromatin Remodeling ATPases BRAHMA and SPLAYED

TL;DR: Using global expression studies, double mutant analysis, and protein interaction assays, overlapping functions are found for the two SWI/SNF ATPases, providing a conceptual framework for understanding the role of SWI-SNF chromatin remodeling in regulation of Arabidopsis development.
Journal ArticleDOI

Engineering drought and salinity tolerance in plants: lessons from genome-wide expression profiling in Arabidopsis.

TL;DR: Examples of how this full-genome expression profiling can contribute to the understanding of complex stress responses and the identification and evaluation of novel transgenes that could hold the key to the development of commercially viable and sustainable crop plants are outlined.
Journal ArticleDOI

Blue-light-mediated shade avoidance requires combined auxin and brassinosteroid action in Arabidopsis seedlings

TL;DR: In this paper, both auxin and brassinosteroids (BR) play an important role in the regulation of enhanced hypocotyl elongation of Arabidopsis seedlings in response to blue light depletion.
References
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Journal ArticleDOI

Gene Ontology: tool for the unification of biology

TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Journal ArticleDOI

Gene Expression Omnibus: NCBI gene expression and hybridization array data repository

TL;DR: The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data and provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-power gene expression and genomic hybridization experiments.
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Analysis of the genome sequence of the flowering plant Arabidopsis thaliana.

TL;DR: This is the first complete genome sequence of a plant and provides the foundations for more comprehensive comparison of conserved processes in all eukaryotes, identifying a wide range of plant-specific gene functions and establishing rapid systematic ways to identify genes for crop improvement.
PatentDOI

Expression monitoring by hybridization to high density oligonucleotide arrays

TL;DR: In this article, the authors proposed a method for monitoring the expression levels of a multiplicity of genes by hybridizing a nucleic acid sample to a high density array of oligonucleotide probes and quantifying the hybridized nucleic acids in the array.
Journal ArticleDOI

Hierarchical Organization of Modularity in Metabolic Networks

TL;DR: It is shown that the metabolic networks of 43 distinct organisms are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units, with their number and degree of clustering following a power law.
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