Results for 'Noise in gene expression'

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  1.  11
    Mechanisms of How Random Input Controls Bursting Gene Expression.Sijia Xiao, Yan Wang, Zhigang Wang & Haohua Wang - 2022 - Complexity 2022:1-17.
    The process of gene expression is affected by many extracellular stimulus signals, and the stochasticity of these signals reshapes gene expression. To adapt the fluctuation of the extracellular environment, genes have many strategies for augmenting their survival probability, frequency modulation, and amplitude modulation. However, it is unclear how genes utilize the stochasticity of signals to regulate gene expression and which strategy will be chosen to maximize cellular function. Here, we analyze a simple mechanistic model (...)
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  2.  64
    Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness.Kunihiko Kaneko - 2011 - Bioessays 33 (6):403-413.
    Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying suchaberrantgene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal (...) expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell‐cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, otheraberrantcellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. (shrink)
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  3.  31
    Post‐Transcriptional Noise Control.Maike M. K. Hansen & Leor S. Weinberger - 2019 - Bioessays 41 (7):1900044.
    Recent evidence indicates that transcriptional bursts are intrinsically amplified by messenger RNA cytoplasmic processing to generate large stochastic fluctuations in protein levels. These fluctuations can be exploited by cells to enable probabilistic bet‐hedging decisions. But large fluctuations in gene expression can also destabilize cell‐fate commitment. Thus, it is unclear if cells temporally switch from high to low noise, and what mechanisms enable this switch. Here, the discovery of a post‐transcriptional mechanism that attenuates noise in HIV is (...)
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  4.  12
    Random sex determination: When developmental noise tips the sex balance.Nicolas Perrin - 2016 - Bioessays 38 (12):1218-1226.
    Sex‐determining factors are usually assumed to be either genetic or environmental. The present paper aims at drawing attention to the potential contribution of developmental noise, an important but often‐neglected component of phenotypic variance. Mutual inhibitions between male and female pathways make sex a bistable equilibrium, such that random fluctuations in the expression of genes at the top of the cascade are sufficient to drive individual development toward one or the other stable state. Evolutionary modeling shows that stochastic sex (...)
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  5.  13
    Disruption of daily rhythms in gene expression: The importance of being synchronised.Alun T. L. Hughes & Hugh D. Piggins - 2014 - Bioessays 36 (7):644-648.
    Extending a normal 24 hours day by four hours is unexpectedly highly disruptive to daily rhythms in gene expression in the blood. Using a paradigm in which human subjects were exposed to a 28 hours day, Archer and colleagues show how this sleep‐altering forced desynchrony protocol caused complex disruption to daily rhythms in distinct groups of genes. Such perturbations in the temporal organisation of the blood transcriptome arise quickly, and point to the fragile nature of coordinated genomic activity. (...)
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  6.  71
    Objective and Subjective Probability in Gene Expression.Joel D. Velasco - 2012 - Progress in Biophysics and Molecular Biology 110:5-10.
    In this paper I address the question of whether the probabilities that appear in models of stochastic gene expression are objective or subjective. I argue that while our best models of the phenomena in question are stochastic models, this fact should not lead us to automatically assume that the processes are inherently stochastic. After distinguishing between models and reality, I give a brief introduction to the philosophical problem of the interpretation of probability statements. I argue that the objective (...)
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  7.  26
    New genes expressed in human brains: Implications for annotating evolving genomes.Yong E. Zhang, Patrick Landback, Maria Vibranovski & Manyuan Long - 2012 - Bioessays 34 (11):982-991.
    New genes have frequently formed and spread to fixation in a wide variety of organisms, constituting abundant sets of lineage‐specific genes. It was recently reported that an excess of primate‐specific and human‐specific genes were upregulated in the brains of fetuses and infants, and especially in the prefrontal cortex, which is involved in cognition. These findings reveal the prevalent addition of new genetic components to the transcriptome of the human brain. More generally, these findings suggest that genomes are continually evolving in (...)
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  8.  16
    Nonsense‐mediated RNA decay: A molecular system micromanaging individual gene activities and suppressing genomic noise.Claudio R. Alonso - 2005 - Bioessays 27 (5):463-466.
    Nonsense‐mediated RNA decay (NMD) is an evolutionary conserved system of RNA surveillance that detects and degrades RNA transcripts containing nonsense mutations. Given that these mutations arise at a relatively low frequency, are there any as yet unknown substrates of NMD in a wild‐type cell? With this question in mind, Mendell et al.1 have used a microarray assay to identify those human genes under NMD regulation. Their results show that, in human cells, NMD regulates hundreds of physiologic transcripts and not just (...)
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  9.  18
    Mitochondria and the non‐genetic origins of cell‐to‐cell variability: More is different.Raúl Guantes, Juan Díaz-Colunga & Francisco J. Iborra - 2016 - Bioessays 38 (1):64-76.
    Gene expression activity is heterogeneous in a population of isogenic cells. Identifying the molecular basis of this variability will improve our understanding of phenomena like tumor resistance to drugs, virus infection, or cell fate choice. The complexity of the molecular steps and machines involved in transcription and translation could introduce sources of randomness at many levels, but a common constraint to most of these processes is its energy dependence. In eukaryotic cells, most of this energy is provided by (...)
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  10.  13
    Shaping research in gene expression: role of the Cambridge Medical Research Council Laboratory of Molecular Biology.Joan A. Steitz - 1986 - Perspectives in Biology and Medicine 29 (3 Pt 2):S90.
  11.  49
    Reprogramming cell fates: reconciling rarity with robustness.Sui Huang - 2009 - Bioessays 31 (5):546-560.
    The stunning possibility of “reprogramming” differentiated somatic cells to express a pluripotent stem cell phenotype (iPS, induced pluripotent stem cell) and the “ground state” character of pluripotency reveal fundamental features of cell fate regulation that lie beyond existing paradigms. The rarity of reprogramming events appears to contradict the robustness with which the unfathomably complex phenotype of stem cells can reliably be generated. This apparent paradox, however, is naturally explained by the rugged “epigenetic landscape” with valleys representing “preprogrammed” attractor states that (...)
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  12.  10
    Beyond the known functions of the CCR4‐NOT complex in gene expression regulatory mechanisms.Marta Ukleja, José María Valpuesta, Andrzej Dziembowski & Jorge Cuellar - 2016 - Bioessays 38 (10):1048-1058.
    Large protein assemblies are usually the effectors of major cellular processes. The intricate cell homeostasis network is divided into numerous interconnected pathways, each controlled by a set of protein machines. One of these master regulators is the CCR4‐NOT complex, which ultimately controls protein expression levels. This multisubunit complex assembles around a scaffold platform, which enables a wide variety of well‐studied functions from mRNA synthesis to transcript decay, as well as other tasks still being identified. Solving the structure of the (...)
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  13.  26
    Gene expression in the twilight of death.Alexander E. Pozhitkov & Peter A. Noble - 2017 - Bioessays 39 (9):1700066.
    After a vertebrate dies, many of its organ systems, tissues, and cells remain functional while its body no longer works as a whole. We define this state as the “twilight of death” − the transition from a living body to a decomposed corpse. We claim that the study of the twilight of death is important to ethical, legal and medical science. We examined gene expression at the twilight of death in the zebrafish and mouse reaching the conclusion that (...)
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  14.  17
    How gene expression in fast‐proliferating cells keeps pace.Rui G. Martinho, Leonardo G. Guilgur & Pedro Prudêncio - 2015 - Bioessays 37 (5):514-524.
    The development of living organisms requires a precise coordination of all basic cellular processes, in space and time. Early embryogenesis of most species with externally deposited eggs starts with a series of extremely fast cleavage cycles. These divisions have a strong influence on gene expression as mitosis represses transcription and pre‐mRNA processing. In this review, we will describe the distinct adaptations for efficient gene expression and discuss the emerging role of the multifunctional NineTeen Complex (NTC) in (...)
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  15. The Full Bayesian Significance Test for Mixture Models: Results in Gene Expression Clustering.Julio Michael Stern, Marcelo de Souza Lauretto & Carlos Alberto de Braganca Pereira - 2008 - Genetics and Molecular Research 7 (3):883-897.
    Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and (...)
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  16.  8
    Does transcriptional heterogeneity facilitate the development of genetic drug resistance?Kevin S. Farquhar, Samira Rasouli Koohi & Daniel A. Charlebois - 2021 - Bioessays 43 (8):2100043.
    Non‐genetic forms of antimicrobial (drug) resistance can result from cell‐to‐cell variability that is not encoded in the genetic material. Data from recent studies also suggest that non‐genetic mechanisms can facilitate the development of genetic drug resistance. We speculate on how the interplay between non‐genetic and genetic mechanisms may affect microbial adaptation and evolution during drug treatment. We argue that cellular heterogeneity arising from fluctuations in gene expression, epigenetic modifications, as well as genetic changes contribute to drug resistance at (...)
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  17.  13
    Analysis and Research of Key Genes in Gene Expression Network Based on Complex Network.Guobin Chen, Jun Qi, Chao Tang, Ying Wang, Yongzhong Wu & Xiaolong Shi - 2020 - Complexity 2020:1-12.
    Gene expression network is also a type of complex network. It is challenging to analyze the gene expression network through relevant knowledge and algorithms of a complex network. In this paper, the existing characteristics of genes are analyzed from various indexes of the gene expression network to analyze key genes and TOP genes. Firstly, gene chip data are screened, gene data with obvious characteristics are selected, and relevant clustering characteristics are analyzed. Then, (...)
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  18. Gene expression patterns in a novel animal appendage: The sea urchin pluteus arm.A. C. Love, M. E. Lee & R. A. Raff - 2007 - Evolution & Development 9:51–68.
    The larval arms of echinoid plutei are used for locomotion and feeding. They are composed of internal calcite skeletal rods covered by an ectoderm layer bearing a ciliary band. Skeletogenesis includes an autonomous molecular differentiation program in primary mesenchyme cells (PMCs), initiated when PMCs leave the vegetal plate for the blastocoel, and a patterning of the differentiated skeletal units that requires molecular cues from the overlaying ectoderm. The arms represent a larval feature that arose in the echinoid lineage during the (...)
     
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  19.  15
    White gene expression, repressive chromatin domains and homeotic gene regulation in Drosophila.Vincenzo Pirrotta & Luca Rastelli - 1994 - Bioessays 16 (8):549-556.
    The use of Drosophila chromosomal rearrangements and transposon constructs involving the white gene reveals the existence of repressive chromatin domains that can spread over considerable genomic distances. One such type of domain is found in heterochromatin and is responsible for classical position‐effect variegation. Another type of repressive domain is established, beginning at specific sequences, by complexes of Polycomb Group proteins. Such complexes, which normally regulate the expression of many genes, including the homeotic loci, are responsible for silencing, white (...)
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  20.  57
    Gene Expression in the Hippocampus in a Rat Model of Premenstrual Dysphoric Disorder After Treatment With Baixiangdan Capsules.Sheng Wei, Peng Sun, Yinghui Guo, Jingxuan Chen, Jieqiong Wang, Chunhong Song, Zifa Li, Ling Xue & Mingqi Qiao - 2018 - Frontiers in Psychology 9.
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  21.  23
    Clocked gene expression in somite formation.Claudio D. Stern & Daniel Vasiliauskas - 1998 - Bioessays 20 (7):528-531.
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  22. The series, the network, and the tree: changing metaphors of order in nature.Olivier Rieppel - 2010 - Biology and Philosophy 25 (4):475-496.
    The history of biological systematics documents a continuing tension between classifications in terms of nested hierarchies congruent with branching diagrams (the ‘Tree of Life’) versus reticulated relations. The recognition of conflicting character distribution led to the dissolution of the scala naturae into reticulated systems, which were then transformed into phylogenetic trees by the addition of a vertical axis. The cladistic revolution in systematics resulted in a representation of phylogeny as a strictly bifurcating pattern (cladogram). Due to the ubiquity of character (...)
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  23.  14
    Transcriptional enhancers play a major role in gene expression.Bruce L. Rogers & Grady F. Saunders - 1986 - Bioessays 4 (2):62-65.
    Transcriptional enhancer sequences have been shown to play a pivotal role in the regulation of some highly expressed genes. First described in eukaryotic viruses, the discovery of enhancers has augmented the previously defined control‐sequence motifs to give a more complete understanding of eukaryotic transcriptional regulatory mechanisms. Some properties of enhancers that distinguish them from other regulatory sequences include their ability to function in a position‐ and orientation‐independent manner. Furthermore, the observation that some enhancers and transcriptional promoters exhibit tissue specificity in (...)
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  24.  40
    Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity.Simone Ecker, Vera Pancaldi, Alfonso Valencia, Stephan Beck & Dirk S. Paul - 2018 - Bioessays 40 (2):1700148.
    Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological (...)
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  25.  24
    Temperature‐controlled Rhythmic Gene Expression in Endothermic Mammals: All Diurnal Rhythms are Equal, but Some are Circadian.Marco Preußner & Florian Heyd - 2018 - Bioessays 40 (7):1700216.
    The circadian clock is a cell autonomous oscillator that controls many aspects of physiology through generating rhythmic gene expression in a time of day dependent manner. In addition, in endothermic mammals body temperature cycles contribute to rhythmic gene expression. These body temperature‐controlled rhythms are hard to distinguish from classic circadian rhythms if analyzed in vivo in endothermic organisms. However, they do not fulfill all criteria of being circadian if analyzed in cell culture or in conditions where (...)
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  26.  27
    On gene expression patterns in mammalian hibernation.Katharine M. Brauch - 2008 - Bioessays 30 (9):920-920.
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  27.  21
    Monoallelic gene expression and mammalian evolution.Barry Keverne - 2009 - Bioessays 31 (12):1318-1326.
    Monoallelic gene expression has played a significant role in the evolution of mammals enabling the expansion of a vast repertoire of olfactory receptor types and providing increased sensitivity and diversity. Monoallelic expression of immune receptor genes has also increased diversity for antigen recognition, while the same mechanism that marks a single allele for preferential rearrangement also provides a distinguishing feature for directing hypermutations. Random monoallelic expression of the X chromosome is necessary to balance gene dosage (...)
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  28.  15
    Stochastic gene expression, disruption of tissue averaging effects and cancer as a disease of development.Jean-Pascal Capp - 2005 - Bioessays 27 (12):1277-1285.
    Despite the extensive literature describing the somatic genetic alterations in cancer cells, the precise origins of cancer cells remain controversial. In this article, I suggest that the etiology of cancer and the generation of genetic instability in cancer cells should be considered in the light of recent findings on both the stochastic nature of gene expression and its regulation at tissue level. By postulating that gene expression is intrinsically probabilistic and that stabilization of gene (...) arises by cellular interactions in “morphogenetic fields”, development and cellular differentiation can be rethought in an evolutionary perspective. In particular, this article proposes that disruptions of cellular interactions are the initial source of abnormal gene expression in cancer cells. Consequently, cancer phenotypes such as genetic and epigenetic instabilities, and also the presence of cells with stem cell‐like properties, may result from inaccurate and aberrant patterns of gene expression generated by microenvironmental alterations. Finally, the therapeutic implications of this view are discussed. BioEssays 27:1277–1285, 2005. © 2005 Wiley Periodicals, Inc. (shrink)
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  29.  12
    Gene expression, cellular diversification and tumor progression to the metastatic phenotype.Garth L. Nicolson - 1991 - Bioessays 13 (7):337-342.
    Alterations in the expression of certain genes or in their products can render benign tumor cells metastatic. Experimentally this has been quickly performed by transferring dominantly acting oncogenes such as c‐H‐rasEJ into susceptible cells, but in vivo such a rapid qualitative change in a dominantly acting oncogene occurs only rarely, and progression to highly metastatic phenotypes is thought to occur through a slow stepwise process. Such slow changes can be reversible and need not involve known dominantly acting oncogenes, consistent (...)
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  30.  22
    Gene expression and the evolution of insect polyphenisms.Jay D. Evans & Diana E. Wheeler - 2001 - Bioessays 23 (1):62-68.
    Polyphenic differences between individuals arise not through differences at the genome level but as a result of specific cues received during development. Polyphenisms often involve entire suites of characters, as shown dramatically by the polyphenic castes found in many social insect colonies. An understanding of the genetic architecture behind polyphenisms provides a novel means of studying the interplay between genomes, gene expression and phenotypes. Here we discuss polyphenisms and molecular genetic tools now available to unravel their developmental bases (...)
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  31.  6
    X‐linked gene expression and sex determination in Caenorhabditis elegans.Philip M. Meneely - 1990 - Bioessays 12 (11):513-518.
    The signal for sex determination in the nematode Caenorhabditis elegans is the ratio between the number of × chromosomes and the number of sets of autosomes (the X/A ratio). Animals with an X/A ratio of 0.67 (a triploid with two × chromosomes) or less are males. Animals with an X/A ratio of 0.75 or more are hermaphrodites. Thus, diploid males have one × chromosome and diploid hermaphrodites have two × chromosomes. However, the difference in X‐chromosome number between the sexes is (...)
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  32.  5
    Regulation of gene expression in developing epidermal epithelia.Carolyn Byrne - 1997 - Bioessays 19 (8):691-698.
    Skin is one of the most thoroughly studied epithelia and can be used as a model for transcriptional control of epithelial differentiation. In particular, the stages of epidermal development and differentiation from a simple epithelium are well characterized. Temporal gene expression during development can be used to assign roles for transcription factors in epidermal differentiation. Approaches to understanding transcriptional regulation in epidermis include extensive promoter analysis and expression studies, in some cases coupled to functional studies. This work (...)
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  33.  14
    Gene expression and the evolution of insect polyphenisms†.Jay D. Evans & Diana E. Wheeler - 2001 - Bioessays 23 (1):62-68.
    Polyphenic differences between individuals arise not through differences at the genome level but as a result of specific cues received during development. Polyphenisms often involve entire suites of characters, as shown dramatically by the polyphenic castes found in many social insect colonies. An understanding of the genetic architecture behind polyphenisms provides a novel means of studying the interplay between genomes, gene expression and phenotypes. Here we discuss polyphenisms and molecular genetic tools now available to unravel their developmental bases (...)
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  34.  7
    Regulation of mitochondrial gene expression in Trypanosoma brucei.Kenneth D. Stuart - 1987 - Bioessays 6 (4):178-181.
    Trypanosoma brucei mitochondria contain unusual small circular DNAs of unknown function. These are catenated with a long informational DNA sequence containing genes homologous to those found in other mitochondria. Although these genes are transcribed throughout the life cycle, differential production of the mitochondrial respiratory system during the life cycle is accompanied by differential abundance of specific transcripts and differential polyadenylation of mitochondrial gene transcripts. Multiple transcripts occur for most of the mitochondrial genes. Transcripts of the apocytochrome b gene (...)
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  35.  75
    Gene expression and the concept of the phenotype.Ohad Nachtomy, Ayelet Shavit & Zohar Yakhini - 2007 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 38 (1):238-254.
    While the definition of the ‘genotype’ has undergone dramatic changes in the transition from classical to molecular genetics, the definition of the ‘phenotype’ has remained for a long time within the classical framework. In addition, while the notion of the genotype has received significant attention from philosophers of biology, the notion of the phenotype has not. Recent developments in the technology of measuring gene-expression levels have made it possible to conceive of phenotypic traits in terms of levels of (...)
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  36.  80
    The molecular and mathematical basis of Waddington's epigenetic landscape: A framework for post‐Darwinian biology?Sui Huang - 2012 - Bioessays 34 (2):149-157.
    The Neo‐Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo‐Darwinism. It needs to (...)
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  37.  22
    DNA Conformation Regulates Gene Expression: The MYC Promoter and Beyond.Olga Zaytseva & Leonie M. Quinn - 2018 - Bioessays 40 (4):1700235.
    Emerging evidence suggests that DNA topology plays an instructive role in cell fate control through regulation of gene expression. Transcription produces torsional stress, and the resultant supercoiling of the DNA molecule generates an array of secondary structures. In turn, local DNA architecture is harnessed by the cell, acting within sensory feedback mechanisms to mediate transcriptional output. MYC is a potent oncogene, which is upregulated in the majority of cancers; thus numerous studies have focused on detailed understanding of its (...)
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  38.  20
    Gene expression during metamorphosis: An ideal model for post‐embryonic development.Jamshed R. Tata - 1993 - Bioessays 15 (4):239-248.
    The precocious induction in vivo and in culture of insect and amphibian metamorphosis by exogenous ecdysteroids and thyroid hormones, and its retardation or inhibition by juvenile hormone and prolactin, respectively, has allowed the analysis of such diverse processes of post‐embryonic development as morphogenesis, tissue remodelling, functional reorganization, and programmed cell death. Metamorphosis in vertebrates also shares many similarities with mammalian development in the late foetal and perinatal period. This review describes the regulation of expression of some of the ‘adult’ (...)
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  39.  16
    Retinoid‐regulated gene expression in normal and leukemic myeloid cells.Peter J. A. Davies, William T. Moore & Michael P. Murtaugh - 1984 - Bioessays 1 (4):160-165.
    Physiological concentrations of retinoic acid can induce acute alterations in the expression of the enzyme tissue transglutaminase in cultured macrophages. The induction of this enzyme offers a probe to study the mechanism of retinoid action in both normal and leukemic cells.
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  40.  19
    Regulation of Gene Expression and Replication Initiation by Non‐Coding Transcription: A Model Based on Reshaping Nucleosome‐Depleted Regions.Julien Soudet & Françoise Stutz - 2019 - Bioessays 41 (11):1900043.
    RNA polymerase II (RNAP II) non‐coding transcription is now known to cover almost the entire eukaryotic genome, a phenomenon referred to as pervasive transcription. As a consequence, regions previously thought to be non‐transcribed are subject to the passage of RNAP II and its associated proteins for histone modification. This is the case for the nucleosome‐depleted regions (NDRs), which provide key sites of entry into the chromatin for proteins required for the initiation of coding gene transcription and DNA replication. In (...)
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  41.  15
    Phytochrome regulation of nuclear gene expression.Jane Silverthorne & Elaine M. Tobin - 1987 - Bioessays 7 (1):18-23.
    Phytochrome is known to regulate the expression of several major nuclearencoded polypeptides at the level of transcription. Both in vivo in vitro methods are currently being used to determine the step(s) between the light activation of phytochrome and changes in gene expression.
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  42.  27
    Serial analysis of gene expression: ESTs get smaller.Mark D. Adams - 1996 - Bioessays 18 (4):261-262.
    Measuring gene expression on a global scale has been one of the vexing problems of cell biology. Velculescu et al.(1) recently proposed a system for identifying gene expression levels based on very short sequence tags – about nine base pairs – located at a specific site within a gene transcript. By coupling the strategy to current automated sequencing machines and the large expressed sequence tag databases, it should be possible to follow changes in gene (...)
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  43.  20
    Serial analysis of gene expression (SAGE): unraveling the bioinformatics tools.Renu Tuteja & Narendra Tuteja - 2004 - Bioessays 26 (8):916-922.
    Serial analysis of gene expression (SAGE) is a powerful technique that can be used for global analysis of gene expression. Its chief advantage over other methods is that it does not require prior knowledge of the genes of interest and provides qualitative and quantitative data of potentially every transcribed sequence in a particular cell or tissue type. This is a technique of expression profiling, which permits simultaneous, comparative and quantitative analysis of gene‐specific, 9‐ to (...)
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  44.  22
    Kenyon Cell Subtypes/Populations in the Honeybee Mushroom Bodies: Possible Function Based on Their Gene Expression Profiles, Differentiation, Possible Evolution, and Application of Genome Editing.Shota Suenami, Satoyo Oya, Hiroki Kohno & Takeo Kubo - 2018 - Frontiers in Psychology 9.
    Honey bees are eusocial insects and the workers inform their nestmates of information regarding the location of food source using symbolic communication, called ‘dance communication’, that are based on their highly advanced learning abilities. Mushroom bodies (MBs), a higher-order center in the honey bee brain, comprise some subtypes/populations of interneurons termed Kenyon cells (KCs) that are distinguished by their cell body size and location in the MBs, as well as their gene expression profiles. Although the role of MBs (...)
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  45.  25
    Multifunctional regulatory proteins that control gene expression in both the nucleus and the cytoplasm.Miles F. Wilkinson & Ann-Bin Shyu - 2001 - Bioessays 23 (9):775-787.
    The multistep pathway of eukaryotic gene expression involves a series of highly regulated events in the nucleus and cytoplasm. In the nucleus, genes are transcribed into pre‐messenger RNAs which undergo a series of nuclear processing steps. Mature mRNAs are then transported to the cytoplasm, where they are translated into protein and degraded at a rate dictated by transcript‐ and cell‐type‐specific cues. Until recently, these individual nuclear and cytoplasmic events were thought to be primarily regulated by different RNA‐ and (...)
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  46.  19
    Altered choroid plexus gene expression in major depressive disorder.Cortney A. Turner, Robert C. Thompson, William E. Bunney, Alan F. Schatzberg, Jack D. Barchas, Richard M. Myers, Huda Akil & Stanley J. Watson - 2014 - Frontiers in Human Neuroscience 8.
  47.  13
    Functional gene expression domains: defining the functional unit of eukaryotic gene regulation.Niall Dillon & Pierangela Sabbattini - 2000 - Bioessays 22 (7):657-665.
    The term functional domain is often used to describe the region containing the cis acting sequences that regulate a gene locus. “Strong” domain models propose that the domain is a spatially isolated entity consisting of a region of extended accessible chromatin bordered by insulators that have evolved to act as functional boundaries. However, the observation that independently regulated loci can overlap partially or completely raises questions about functional requirements for physically isolated domain structures. An alternative model, the “weak” domain (...)
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  48.  45
    Control involving metabolism and Gene expression.Hans V. Westerhoff & Daniel Kahn - 1993 - Acta Biotheoretica 41 (1-2):75-83.
    Control of DNA supercoiling by the free-energy of hydrolysis of ATP that involves gene expression is analyzed in terms of three levels of unconnected metabolic pathways. These are synthesis and breakdown of topoisomerase mRNAs, synthesis and breakdown of topoisomerase proteins and supercoiling and relaxation of DNA. The so-called square-matrix method previously developed for the control of metabolic pathways, is extended to deal with this hierarchical control system. It turns out that also in this case, the matrix of control (...)
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  49.  16
    Genome analysis with gene expression microarrays.Mark Schena - 1996 - Bioessays 18 (5):427-431.
    Advances in biochemistry, chemistry and engineering have enabled the development of a new gene expression assay. This ‘chip‐based’ approach utilizes microscopic arrays of cDNAs printed on glass as high‐density hybridization targets. Fluorescent probe mixtures derived from total cellular messenger RNA (mRNA) hybridize to cognate elements on the array, allowing accurate measurement of the expression of the corresponding genes. Array densities of >1,000 cDNAs per cm2 enable quantitative expression monitoring of a large number of genes in a (...)
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  50.  18
    Induction of plant gene expression by light.William F. Thompson, L. S. Kaufman & J. C. Watson - 1985 - Bioessays 3 (4):153-159.
    Light effects on the activity of several genes have recently been exploited in studies of plant gene expression. We discuss here some examples involving nuclear genes of higher plants, with emphasis on responses mediated by the phytochrome system. Recent work has revealed considerable diversity in the responses of different genes, indicating that several different regulatory programs are probably involved. A start has been made in studies of nuclear events associated with the changes in expression. Transcriptional regulation almost (...)
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