Analyzing time series gene expression data
暂无分享,去创建一个
[1] D. Botstein,et al. The transcriptional program of sporulation in budding yeast. , 1998, Science.
[2] Ronald W. Davis,et al. A genome-wide transcriptional analysis of the mitotic cell cycle. , 1998, Molecular cell.
[3] Michael Ruogu Zhang,et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.
[4] J. Mesirov,et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.
[5] Ron Shamir,et al. Clustering Gene Expression Patterns , 1999, J. Comput. Biol..
[6] U. Alon,et al. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[7] D. Botstein,et al. Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[8] Patrik D'haeseleer,et al. Linear Modeling of mRNA Expression Levels During CNS Development and Injury , 1998, Pacific Symposium on Biocomputing.
[9] J. Mesirov,et al. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[10] D. Botstein,et al. Singular value decomposition for genome-wide expression data processing and modeling. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[11] Yudong D. He,et al. Functional Discovery via a Compendium of Expression Profiles , 2000, Cell.
[12] D. Botstein,et al. Two yeast forkhead genes regulate the cell cycle and pseudohyphal growth , 2000, Nature.
[13] Roded Sharan,et al. CLICK: A Clustering Algorithm for Gene Expression Analysis , 2000, ISMB 2000.
[14] Michal Linial,et al. Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..
[15] Richard M. Karp,et al. Universal DNA tag systems: a combinatorial design scheme , 2000, RECOMB '00.
[16] Neal S. Holter,et al. Fundamental patterns underlying gene expression profiles: simplicity from complexity. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[17] D. Botstein,et al. Genomic expression programs in the response of yeast cells to environmental changes. , 2000, Molecular biology of the cell.
[18] Michal Linial,et al. Using Bayesian networks to analyze expression data , 2000, RECOMB '00.
[19] George M. Church,et al. Aligning gene expression time series with time warping algorithms , 2001, Bioinform..
[20] Neal S. Holter,et al. Dynamic modeling of gene expression data. , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[21] Nicola J. Rinaldi,et al. Serial Regulation of Transcriptional Regulators in the Yeast Cell Cycle , 2001, Cell.
[22] L. P. Zhao,et al. Statistical modeling of large microarray data sets to identify stimulus-response profiles , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[23] M. Gerstein,et al. Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions. , 2001, Journal of molecular biology.
[24] Nir Friedman,et al. Inferring subnetworks from perturbed expression profiles , 2001, ISMB.
[25] Russ B. Altman,et al. Missing value estimation methods for DNA microarrays , 2001, Bioinform..
[26] Joshua M. Stuart,et al. A Gene Expression Map for Caenorhabditis elegans , 2001, Science.
[27] M. Marton,et al. Transcriptional Profiling Shows that Gcn4p Is a Master Regulator of Gene Expression during Amino Acid Starvation in Yeast , 2001, Molecular and Cellular Biology.
[28] Kerby Shedden,et al. Analysis of cell-cycle gene expression in Saccharomyces cerevisiae using microarrays and multiple synchronization methods , 2002, Nucleic Acids Res..
[29] L. Breeden,et al. Conserved homeodomain proteins interact with MADS box protein Mcm1 to restrict ECB-dependent transcription to the M/G1 phase of the cell cycle. , 2002, Genes & development.
[30] David Page,et al. Modelling regulatory pathways in E. coli from time series expression profiles , 2002, ISMB.
[31] B. S. Baker,et al. Gene Expression During the Life Cycle of Drosophila melanogaster , 2002, Science.
[32] John T. Dimos,et al. A Stem Cell Molecular Signature , 2002, Science.
[33] Juliane Fluck,et al. Microarrays: how many do you need? , 2002, RECOMB '02.
[34] C. Ball,et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. , 2002, Molecular biology of the cell.
[35] Nicola J. Rinaldi,et al. Transcriptional Regulatory Networks in Saccharomyces cerevisiae , 2002, Science.
[36] Kai-Florian Storch,et al. Extensive and divergent circadian gene expression in liver and heart , 2002, Nature.
[37] E. Lander,et al. Human macrophage activation programs induced by bacterial pathogens , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[38] K. Shedden,et al. Analysis of cell-cycle-specific gene expression in human cells as determined by microarrays and double-thymidine block synchronization , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[39] S. Dudoit,et al. STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS , 2002 .
[40] B. H. Miller,et al. Coordinated Transcription of Key Pathways in the Mouse by the Circadian Clock , 2002, Cell.
[41] Paola Sebastiani,et al. Cluster analysis of gene expression dynamics , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[42] Aurélien Mazurie,et al. Gene networks inference using dynamic Bayesian networks , 2003, ECCB.
[43] D. Botstein,et al. Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[44] Alexander Schliep,et al. Using hidden Markov models to analyze gene expression time course data , 2003, ISMB.
[45] Erik D. Demaine,et al. K-ary Clustering with Optimal Leaf Ordering for Gene Expression Data , 2002, WABI.
[46] Dirk Husmeier,et al. Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks , 2003, Bioinform..
[47] Tommi S. Jaakkola,et al. Continuous Representations of Time-Series Gene Expression Data , 2003, J. Comput. Biol..
[48] T. Jaakkola,et al. Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[49] Satoru Miyano,et al. Inferring gene networks from time series microarray data using dynamic Bayesian networks , 2003, Briefings Bioinform..
[50] Zhaohui S. Qin,et al. Statistical resynchronization and Bayesian detection of periodically expressed genes. , 2004, Nucleic acids research.
[51] Stephen D. Bay,et al. Temporal Aggregation Bias and Inference of Causal Regulatory Networks , 2004, J. Comput. Biol..
[52] Korbinian Strimmer,et al. Identifying periodically expressed transcripts in microarray time series data , 2008, Bioinform..
[53] I. Simon,et al. Deconvolving cell cycle expression data with complementary information , 2004, ISMB/ECCB.