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
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Cks1-dependent proteasome recruitment and activation of CDC20 transcription in budding yeast
May C. Morris,Peter K. Kaiser,Peter K. Kaiser,Stanislav G. Rudyak,Christopher Baskerville,Mark H. Watson,Steven I. Reed +6 more
TL;DR: It is shown that the essential role of Cks1 in Saccharomyces cerevisiae is primarily involved in promoting mitosis by modulating the transcriptional activation of the APC/C protein–ubiquitin ligase activator Cdc20.
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The peroxisomal membrane protein Inp2p is the peroxisome-specific receptor for the myosin V motor Myo2p of Saccharomyces cerevisiae.
TL;DR: This work has identified Inp2p as the peroxisome-specific receptor for Myo2p, the first per oxisomal protein implicated in the vectorial movement ofPeroxisomes.
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Bioinformatics Analysis of Experimentally Determined Protein Complexes in the Yeast Saccharomyces cerevisiae
TL;DR: It is demonstrated quantitatively that protein complexes in the yeast Saccharomyces cerevisiae are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or nonessential), and share identical functional classification and cellular localization.
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Clustering microarray gene expression data using weighted Chinese restaurant process
TL;DR: An improved model-based Bayesian approach to cluster microarray gene expression data that shows that as much as 30% of significant genes clustered in the same group display complex relationships with the consensus pattern of the cluster.
Journal ArticleDOI
Reconstructing cell cycle pseudo time-series via single-cell transcriptome data.
Zehua Liu,Huazhe Lou,Kaikun Xie,Hao Wang,Ning Chen,Oscar M. Aparicio,Michael Q. Zhang,Michael Q. Zhang,Rui Jiang,Ting Chen,Ting Chen +10 more
TL;DR: A computational model is introduced to reconstruct a pseudo-time series from single cell transcriptome data, identify the cell cycle stages, identify candidate cell cycle-regulated genes and recover the methylome changes during thecell cycle.
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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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.
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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.