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Open AccessJournal ArticleDOI

Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization

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TLDR
A comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle is created, and it is found that the mRNA levels of more than half of these 800 genes respond to one or both of these cyclins.
Abstract
We sought to create a comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle. To this end, we used DNA microarrays and samples from yeast cultures sync...

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Citations
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Journal ArticleDOI

Spatial distributions of expansion rate, cell division rate and cell size in maize leaves: a synthesis of the effects of soil water status, evaporative demand and temperature

TL;DR: The size of epidermal and of mesophyll cells was nearly unaffected in the leaf zone with both cell division and tissue expansion, suggesting that water deficit affects tissue expansion rate and cell division rate to the same extent.
Journal ArticleDOI

Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

TL;DR: The authors' rigorous analysis of gene expression microarray profiles using RMT has showed that the transition of NNSD of correlation matrix of microarray profile provides a profound theoretical criterion to determine the correlation threshold for identifying gene co-expression networks.
Proceedings ArticleDOI

TRICLUSTER: an effective algorithm for mining coherent clusters in 3D microarray data

TL;DR: A novel algorithm, TRICLUSTER, for mining coherent clusters in three-dimensional (3D) gene expression datasets, which can mine arbitrarily positioned and overlapping clusters, and depending on different parameter values, it can mine different types of clusters.
Journal ArticleDOI

The application of DNA microarrays in gene expression analysis

TL;DR: How DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants, and data handling are discussed.
Journal ArticleDOI

Discovery of biological networks from diverse functional genomic data.

TL;DR: A general probabilistic system for query-based discovery of pathway-specific networks through integration of diverse genome-wide data for Saccharomyces cerevisiae and experimentally verifying predictions for the process of chromosomal segregation.
References
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Journal ArticleDOI

Cluster analysis and display of genome-wide expression patterns

TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Journal ArticleDOI

Real time quantitative PCR.

TL;DR: Unlike other quantitative PCR methods, real-time PCR does not require post-PCR sample handling, preventing potential PCR product carry-over contamination and resulting in much faster and higher throughput assays.
Journal ArticleDOI

Exploring the Metabolic and Genetic Control of Gene Expression on a Genomic Scale

TL;DR: DNA microarrays containing virtually every gene of Saccharomyces cerevisiae were used to carry out a comprehensive investigation of the temporal program of gene expression accompanying the metabolic shift from fermentation to respiration, and the expression patterns of many previously uncharacterized genes provided clues to their possible functions.
Book ChapterDOI

Getting started with yeast.

TL;DR: The yeast Saccharomyces cerevisiae is now recognized as a model system representing a simple eukaryote whose genome can be easily manipulated and made particularly accessible to gene cloning and genetic engineering techniques.
Journal ArticleDOI

A Genome-Wide Transcriptional Analysis of the Mitotic Cell Cycle

TL;DR: The genome-wide characterization of mRNA transcript levels during the cell cycle of the budding yeast S. cerevisiae indicates a mechanism for local chromosomal organization in global mRNA regulation and links a range of human genes to cell cycle period-specific biological functions.
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