Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization
Paul T. Spellman,Gavin Sherlock,Gavin Sherlock,Michael Q. Zhang,Vishwanath R. Iyer,Kirk R. Anders,Michael B. Eisen,Patrick O. Brown,Patrick O. Brown,David Botstein,Bruce Futcher +10 more
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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...read more
Citations
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Journal ArticleDOI
Classification using functional data analysis for temporal gene expression data
Xiaoyan Leng,Hans-Georg Müller +1 more
TL;DR: This work proposes a method of classifying collections of temporal gene expression curves in which individual expression profiles are modeled as independent realizations of a stochastic process, and demonstrates that this methodology provides low-error-rate classification for both yeast cell-cycle gene expression profiles and Dictyostelium cell-type specific gene expression patterns.
Journal ArticleDOI
Deciphering gene expression regulatory networks.
John J. Wyrick,Richard A. Young +1 more
TL;DR: The recent description of the genetic network controlling the cell cycle illustrates the tremendous potential of genome-wide location and expression analysis approaches for deciphering gene expression regulatory networks in eukaryotic cells.
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Statistical significance of variables driving systematic variation in high-dimensional data.
TL;DR: The jackstraw is introduced, a new approach called the Jackstraw that allows one to accurately identify genomic variables that are statistically significantly associated with any subset or linear combination of PCs and can greatly simplify complex significance testing problems encountered in genomics.
Journal ArticleDOI
Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.
TL;DR: A simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure and guarantees to eventually find the globally optimal distribution of genes over clusters.
Journal ArticleDOI
Design of studies using DNA microarrays.
TL;DR: This work reviews several types of objectives of studies using DNA microarrays and addresses issues such as selection of samples, levels of replication needed, allocation of samples to dyes and arrays, sample size considerations, and analysis strategies.
References
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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.
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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
Raymond J. Cho,Michael J. Campbell,Elizabeth A. Winzeler,Lars M. Steinmetz,Andrew R. Conway,Lisa Wodicka,Tyra G. Wolfsberg,Andrei Gabrielian,David Landsman,David J. Lockhart,Ronald W. Davis +10 more
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.