Broad distribution spectrum from Gaussian to power law appears in stochastic variations in RNA-seq data

[1]  Stefan Thurner,et al.  Introduction to Complex Systems , 2018, Oxford Scholarship Online.

[2]  Keisuke Fujita,et al.  Transcriptional bursting is intrinsically caused by interplay between RNA polymerases on DNA , 2016, Nature Communications.

[3]  A. Nagano,et al.  RNA-Seq reveals virus–virus and virus–plant interactions in nature , 2016, FEMS microbiology ecology.

[4]  Gil Stelzer,et al.  Elucidating tissue specific genes using the Benford distribution , 2016, BMC Genomics.

[5]  M. Birtwistle,et al.  A Mechanistic Beta-Binomial Probability Model for mRNA Sequencing Data , 2016, PloS one.

[6]  G. Barton,et al.  How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? , 2015, RNA.

[7]  G. Barton,et al.  Erratum: How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? , 2016, RNA.

[8]  A. Nagano,et al.  Noise-plasticity correlations of gene expression in the multicellular organism Arabidopsis thaliana. , 2015, Journal of theoretical biology.

[9]  Christian Cole,et al.  Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment , 2015, Bioinform..

[10]  M. Mihara,et al.  Detection of plant viruses in natural environments by using RNA-Seq. , 2015, Methods in molecular biology.

[11]  Rob Phillips,et al.  Promoter architecture dictates cell-to-cell variability in gene expression , 2014, Science.

[12]  Tetsushi Sakuma,et al.  Stochastic promoter activation affects Nanog expression variability in mouse embryonic stem cells , 2014, Scientific Reports.

[13]  H. Woods.  Mosaic physiology from developmental noise: within-organism physiological diversity as an alternative to phenotypic plasticity and phenotypic flexibility , 2014, Journal of Experimental Biology.

[14]  Ido Golding,et al.  Genetic Determinants and Cellular Constraints in Noisy Gene Expression , 2013, Science.

[15]  G. Singh.  Coupling Between Noise and Plasticity in E. coli , 2013, G3: Genes, Genomes, Genetics.

[16]  C. Mason,et al.  Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data , 2013, Genome Biology.

[17]  M. Mihara,et al.  Deciphering and Prediction of Transcriptome Dynamics under Fluctuating Field Conditions , 2012, Cell.

[18]  Mats E. Pettersson,et al.  Inheritance Beyond Plain Heritability: Variance-Controlling Genes in Arabidopsis thaliana , 2012, PLoS genetics.

[19]  J. F. Poyatos,et al.  Balancing noise and plasticity in eukaryotic gene expression , 2012, BMC Genomics.

[20]  G. Galili,et al.  Deciphering energy-associated gene networks operating in the response of Arabidopsis plants to stress and nutritional cues. , 2012, The Plant journal : for cell and molecular biology.

[21]  U. Alon,et al.  Correction: A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli , 2012, PLoS Genetics.

[22]  Albert Libchaber,et al.  Universal protein fluctuations in populations of microorganisms. , 2012, Physical review letters.

[23]  A. van Oudenaarden,et al.  Using Gene Expression Noise to Understand Gene Regulation , 2012, Science.

[24]  U. Alon,et al.  A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli , 2012, PLoS genetics.

[25]  R. Segev,et al.  GENERAL PROPERTIES OF THE TRANSCRIPTIONAL TIME-SERIES IN ESCHERICHIA COLI , 2011, Nature Genetics.

[26]  K. Kaneko,et al.  Fluctuation and response in biology , 2010, Cellular and Molecular Life Sciences.

[27]  Ben Lehner.  Conflict between Noise and Plasticity in Yeast , 2010, PLoS genetics.

[28]  Paul J. Choi,et al.  Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells , 2010, Science.

[29]  Michael P. Snyder,et al.  RNA‐Seq: A Method for Comprehensive Transcriptome Analysis , 2010, Current protocols in molecular biology.

[30]  C. Lim,et al.  Regulated Fluctuations in Nanog Expression Mediate Cell Fate Decisions in Embryonic Stem Cells , 2009, PLoS biology.

[31]  Young-Joon Kim,et al.  Intrinsic variability of gene expression encoded in nucleosome positioning sequences , 2009, Nature Genetics.

[32]  David Meinke,et al.  Identifying essential genes in Arabidopsis thaliana. , 2008, Trends in plant science.

[33]  M. Stephens,et al.  RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. , 2008, Genome research.

[34]  Kazuo Shinozaki,et al.  The AtGenExpress hormone and chemical treatment data set: experimental design, data evaluation, model data analysis and data access. , 2008, The Plant journal : for cell and molecular biology.

[35]  N. Barkai,et al.  Two strategies for gene regulation by promoter nucleosomes. , 2008, Genome research.

[36]  B. Williams,et al.  Mapping and quantifying mammalian transcriptomes by RNA-Seq , 2008, Nature Methods.

[37]  Hannah H. Chang,et al.  Transcriptome-wide noise controls lineage choice in mammalian progenitor cells , 2008, Nature.

[38]  A. Konagaya,et al.  Coincidence between Transcriptome Analyses on Different Microarray Platforms Using a Parametric Framework , 2008, PloS one.

[39]  G. Galili,et al.  Principal Transcriptional Programs Regulating Plant Amino Acid Metabolism in Response to Abiotic Stresses1[W][OA] , 2008, Plant Physiology.

[40]  Jung Kyoon Choi,et al.  Epigenetic regulation and the variability of gene expression , 2008, Nature Genetics.

[41]  M. Robinson,et al.  Small-sample estimation of negative binomial dispersion, with applications to SAGE data. , 2007, Biostatistics.

[42]  E. Bornberg-Bauer,et al.  The AtGenExpress global stress expression data set: protocols, evaluation and model data analysis of UV-B light, drought and cold stress responses. , 2007, The Plant journal : for cell and molecular biology.

[43]  Michael Karin,et al.  Genetic Properties Influencing the Evolvability of Gene Expression , 2007 .

[44]  Nir Friedman,et al.  Linking stochastic dynamics to population distribution: an analytical framework of gene expression. , 2006, Physical review letters.

[45]  Jennifer L. Nemhauser,et al.  Different Plant Hormones Regulate Similar Processes through Largely Nonoverlapping Transcriptional Responses , 2006, Cell.

[46]  J. Derisi,et al.  Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise , 2006, Nature.

[47]  金子 邦彦,et al.  Life : an introduction to complex systems biology , 2006 .

[48]  E. Cox,et al.  Real-Time Kinetics of Gene Activity in Individual Bacteria , 2005, Cell.

[49]  T. Elston,et al.  Stochasticity in gene expression: from theories to phenotypes , 2005, Nature Reviews Genetics.

[50]  Kunihiko Kaneko,et al.  Ubiquity of log-normal distributions in intra-cellular reaction dynamics , 2005, Biophysics.

[51]  Akiko Maruyama-Nakashita,et al.  Identification of a novel cis-acting element conferring sulfur deficiency response in Arabidopsis roots. , 2005, The Plant journal : for cell and molecular biology.

[52]  Yoichiro Ito,et al.  On the relation between fluctuation and response in biological systems , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[53]  M. Murakami,et al.  The Homeoprotein Nanog Is Required for Maintenance of Pluripotency in Mouse Epiblast and ES Cells , 2003, Cell.

[54]  Mads Kærn,et al.  Noise in eukaryotic gene expression , 2003, Nature.

[55]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.