Gotowe bibliografie tematyczne / Transcriptional Regulation

Gotowa bibliografia na temat „Transcriptional Regulation”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 25 maja 2024

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Artykuły w czasopismach na temat "Transcriptional Regulation"

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Cornut, Maxence, Emilie Bourdonnay i Thomas Henry. "Transcriptional Regulation of Inflammasomes". International Journal of Molecular Sciences 21, nr 21 (29.10.2020): 8087. http://dx.doi.org/10.3390/ijms21218087.

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Inflammasomes are multimolecular complexes with potent inflammatory activity. As such, their activity is tightly regulated at the transcriptional and post-transcriptional levels. In this review, we present the transcriptional regulation of inflammasome genes from sensors (e.g., NLRP3) to substrates (e.g., IL-1β). Lineage-determining transcription factors shape inflammasome responses in different cell types with profound consequences on the responsiveness to inflammasome-activating stimuli. Pro-inflammatory signals (sterile or microbial) have a key transcriptional impact on inflammasome genes, which is largely mediated by NF-κB and that translates into higher antimicrobial immune responses. Furthermore, diverse intrinsic (e.g., circadian clock, metabolites) or extrinsic (e.g., xenobiotics) signals are integrated by signal-dependent transcription factors and chromatin structure changes to modulate transcriptionally inflammasome responses. Finally, anti-inflammatory signals (e.g., IL-10) counterbalance inflammasome genes induction to limit deleterious inflammation. Transcriptional regulations thus appear as the first line of inflammasome regulation to raise the defense level in front of stress and infections but also to limit excessive or chronic inflammation.
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Lee, Pauline, Truksa Jaroslav, Hongfan Peng i Ernest Beutler. "Transcriptional Regulation of Hepcidin by Iron." Blood 110, nr 11 (16.11.2007): 2664. http://dx.doi.org/10.1182/blood.v110.11.2664.2664.

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Abstract Transcriptional regulation by iron in mammalian systems is poorly understood. Hepcidin, a 25 amino acid peptide that plays a central role in iron homeostasis, is transcriptionally regulated by iron. A region of the murine hepcidin promoter 1.6 to 1.8 kb upstream from the start of translation was recently identified to be important in transcriptional regulation by iron (Truksa J, et al. The distal location of the iron responsive region of the hepcidin promoter. Blood DOI 10.1182/blood-2007-05-091108, 2007). In order to identify transcription factors that might be important in regulation by iron, transcription factor microarray analyses (Panomics TranSignal Protein/DNA Array) were performed with nuclear extracts from livers of mice made iron deficient or iron loaded for 4 weeks. The analyses revealed 43 transcription factors that were upregulated in iron loaded liver nuclear extracts and 39 transcription factors that were upregulated in iron deficient nuclear extracts. In the region of the promoter we had found essential for transcriptional regulation by iron, −1.6 to −1.8 kb, consensus motifs were identified by Genomatix MatInspector for 10 transcription factors that corresponded to transcription factors upregulated in high iron nuclear extracts by array analyses. Similarly, the consensus sequences for 5 transcription factors corresponded to transcription factors identified in iron deficient nuclear extracts. Electrophoretic mobility shift assays were performed with probes across this region of the murine hepcidin promoter. Several probes exhibited differential binding between deficient and high iron nuclear extracts. These include the probe encompassing the CCAAT box and MEL1 motif, a probe containing a HLH motif, and a probe containing a bZIP and COUP motif. The probe containing the CCAAT motif was supershifted with antibodies against CBF, but was not supershifted with antibodies against SMAD4, CEBPα, and COUP. The probe containing a bZIP and COUP motif can be supershifted with antibodies against COUP-Tf and HNF4α, but not with antibodies against SMAD4, CEBPα, and COUP. Our data suggest that CBFA, COUP, and HNF4α are involved in transcriptional regulation of hepcidin by iron.
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Wilson, Nicola K., Fernando J. Calero-Nieto, Rita Ferreira i Berthold Göttgens. "Transcriptional regulation of haematopoietic transcription factors". Stem Cell Research & Therapy 2, nr 1 (2011): 6. http://dx.doi.org/10.1186/scrt47.

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Hahn, Steven. "Transcriptional regulation". EMBO reports 9, nr 7 (6.06.2008): 612–16. http://dx.doi.org/10.1038/embor.2008.99.

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Helntz, Nathaniel. "Transcriptional regulation". Trends in Biochemical Sciences 16 (styczeń 1991): 393. http://dx.doi.org/10.1016/0968-0004(91)90161-n.

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Dutta, Chaitali, Prasanta K. Patel, Adam Rosebrock, Anna Oliva, Janet Leatherwood i Nicholas Rhind. "The DNA Replication Checkpoint Directly Regulates MBF-Dependent G1/S Transcription". Molecular and Cellular Biology 28, nr 19 (28.07.2008): 5977–85. http://dx.doi.org/10.1128/mcb.00596-08.

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ABSTRACT The DNA replication checkpoint transcriptionally upregulates genes that allow cells to adapt to and survive replication stress. Our results show that, in the fission yeast Schizosaccharomyces pombe, the replication checkpoint regulates the entire G1/S transcriptional program by directly regulating MBF, the G1/S transcription factor. Instead of initiating a checkpoint-specific transcriptional program, the replication checkpoint targets MBF to maintain the normal G1/S transcriptional program during replication stress. We propose a mechanism for this regulation, based on in vitro phosphorylation of the Cdc10 subunit of MBF by the Cds1 replication-checkpoint kinase. Replacement of two potential phosphorylation sites with phosphomimetic amino acids suffices to promote the checkpoint transcriptional program, suggesting that Cds1 phosphorylation directly regulates MBF-dependent transcription. The conservation of MBF between fission and budding yeast, and recent results implicating MBF as a target of the budding yeast replication checkpoint, suggests that checkpoint regulation of the MBF transcription factor is a conserved strategy for coping with replication stress. Furthermore, the structural and regulatory similarity between MBF and E2F, the metazoan G1/S transcription factor, suggests that this checkpoint mechanism may be broadly conserved among eukaryotes.
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Shimizu, Kiminori, Julie K. Hicks, Tzu-Pi Huang i Nancy P. Keller. "Pka, Ras and RGS Protein Interactions Regulate Activity of AflR, a Zn(II)2Cys6 Transcription Factor in Aspergillus nidulans". Genetics 165, nr 3 (1.11.2003): 1095–104. http://dx.doi.org/10.1093/genetics/165.3.1095.

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Abstract Sterigmatocystin (ST) is a carcinogenic polyketide produced by several filamentous fungi including Aspergillus nidulans. Expression of ST biosynthetic genes (stc genes) requires activity of a Zn(II)2Cys6 transcription factor, AflR. aflR is transcriptionally and post-transcriptionally regulated by a G-protein/cAMP/protein kinase A (PkaA) signaling pathway involving FlbA, an RGS (regulator of G-protein signaling) protein. Prior genetic data showed that FlbA transcriptional regulation of aflR was PkaA dependent. Here we show that mutation of three PkaA phosphorylation sites in AflR allows resumption of stc expression in an overexpression pkaA background but does not remediate stc expression in a ΔflbA background. This demonstrates negative regulation of AflR activity by phosphorylation and shows that FlbA post-transcriptional regulation of aflR is PkaA independent. AflR nucleocytoplasmic location further supports PkaA-independent regulation of AflR by FlbA. GFP-tagged AflR is localized to the cytoplasm when pkaA is overexpressed but nuclearly located in a ΔflbA background. aflR is also transcriptionally and post-transcriptionally regulated by RasA. RasA transcriptional control of aflR is PkaA independent but RasA post-transcriptional control of AflR is partially mediated by PkaA.
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Geng, Yanbiao, Peter Laslo, Kevin Barton i Chyung-Ru Wang. "Transcriptional Regulation ofCD1D1by Ets Family Transcription Factors". Journal of Immunology 175, nr 2 (7.07.2005): 1022–29. http://dx.doi.org/10.4049/jimmunol.175.2.1022.

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Hermsen, Rutger, Sander Tans i Pieter Rein ten Wolde. "Transcriptional Regulation by Competing Transcription Factor Modules". PLoS Computational Biology 2, nr 12 (2006): e164. http://dx.doi.org/10.1371/journal.pcbi.0020164.

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Hermsen, Rutger, Sander J. Tans i Pieter Rein ten Wolde. "Transcriptional Regulation by Competing Transcription Factor Modules". PLoS Computational Biology preprint, nr 2006 (2005): e164. http://dx.doi.org/10.1371/journal.pcbi.0020164.eor.

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Rozprawy doktorskie na temat "Transcriptional Regulation"

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Adegoke, Oluwajoba Oluwapelumi. "Transcriptional and post-transcriptional regulation in testicular toxicity". Thesis, University of Leicester, 2015. http://hdl.handle.net/2381/31979.

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The control of gene expression occurs at multiple levels one of which is controlled by epigenetic regulation. In this work, it was hypothesised that changes in DNA methylation (transcriptional level) and miRNA expression (post-transcriptional level) might be involved in the mechanism of compound-induced testicular toxicity. mRNA and miRNA analysis of mouse testis was performed following exposure to dibutyl phthalate, 17β-estradiol and doxorubicin. Pathway analysis of transcriptional changes revealed all three chemicals interfered with the steroidogenic pathway, with further modulation of oxidative stress pathways in doxorubicin models. Doxorubicin exhibited a profound effect on the testis by decreasing the expression of germ cell-specific transcripts and increasing the expression of Leydig cell transcripts, apoptotic genes and pro-apoptotic miRNAs (miR-145, miR-26a, miR29 family). The post-transcriptional regulatory activity of these proapoptotic miRNAs was demonstrated by decreased transcript expression of their target DNA-methyl transferases (Dnmt) transcripts. An extensive deregulation of DNA methylation was observed that could be a consequence of altered Dnmts levels. Hypomethylation of genes, such as Cdkn2a and Pcna2, led to activation of p53 signaling. The same experiment was repeated in in vitro models of the testis. Pathway analysis revealed miRNA-mRNAs regulation of signaling pathways between germ cell-Sertoli cell and Sertoli cell-Sertoli cell junctions. A systematic review was conducted to establish the role of epigenetic-mediated mechanisms in toxicant-induced male reproductive toxicity. The study identified that decrease in Dnmt levels following chemical exposure could play a role in germ cell apoptosis. Also, the aberrant methylation of H19 could serve as a useful biomarker in the transgenerational effects of chemicals. The findings from this project provide further insight into the mechanisms of compound-induced testicular toxicity, through the utilization of genomics and a systematic review approach to published work. It identified epigenetic mechanisms both at the transcriptional and post-transcriptional levels are involved in the mechanism of toxicity.
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Dennis, Jonathan Hancock. "Transcriptional regulation by Brn 3 POU domain containing transcription factors". Thesis, University College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.249684.

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Koutsoulidou, Andrie. "Investigation of transcriptional and post-transcriptional regulation of myogenesis". Thesis, University of Bristol, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.559081.

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Skeletal myogenesis IS a complicated and tightly regulated process, at both transcriptional and post-transcriptional levels. Muscle cells isolated from different stages of the human foetal development displayed increased capacity to differentiate in vitro at late stages of the development. Twist is an early developmental transcription factor shown to inhibit muscle differentiation in mice. Endogenous human TWIST (H-TWIST) protein levels were found to be inversely proportional to the state of foetal muscle development and the capacity of isolated myoblasts to differentiate in vitro. Investigation of H-TWIST gene transcriptional regulation revealed that endogenous MyoD binds to the H- TWIST promoter and inhibits its expression. Overexpression of MyoD increased the low capacity of human foetal myoblasts to differentiation in vitro and decreased the levels of H- TWIST protein. These results propose a mechanism by which MyoD downregulates the expression of H-TWIST gene, thus promoting myogenesis. MicroRNAs are non-coding RNA molecules that post-transcriptionally regulate many cellular processes. MiR-l, miR- 133a, miR-133b and miR-206, also known as myomiRs, are expressed in muscle tissue and induced during muscle cell differentiation. MyomiRs were found to be increased during late stages of human foetal muscle development. Increases in their expression levels were proportional to the capacity of myoblasts to differentiate in vitro. Changes in myomiR levels during human foetal development were accompanied by endogenous alterations in their known targets and also in their inducer, MyoD. Overexpression of the latter resulted in an induction of muscle cell differentiation in vitro, accompanied by an increase in the levels of miR-l, miR-133a, miR-133b and miR-206. Myotonic dystrophy type 1 is a muscular dystrophy characterized by impaired muscle cell differentiation. Muscle cells isolated from DMl patients from distinct developmental stages showed a reduction in the expression levels of myomiRs during both differentiated and undifferentiated stages, verifying their important role during myogenesis.
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Asif, Hafiz Muhammad Shahzad. "Inference dynamics in transcriptional regulation". Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6238.

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Computational systems biology is an emerging area of research that focuses on understanding the holistic view of complex biological systems with the help of statistical, mathematical and computational techniques. The regulation of gene expression in gene regulatory network is a fundamental task performed by all known forms of life. In this subsystem, modelling the behaviour of the components and their interactions can provide useful biological insights. Statistical approaches for understanding biological phenomena such as gene regulation are proving to be useful for understanding the biological processes that are otherwise not comprehensible due to multitude of information and experimental difficulties. A combination of both the experimental and computational biology can potentially lead to system level understanding of biological systems. This thesis focuses on the problem of inferring the dynamics of gene regulation from the observed output of gene expression. Understanding of the dynamics of regulatory proteins in regulating the gene expression is a fundamental task in elucidating the hidden regulatory mechanisms. For this task, an initial fixed structure of the network is obtained using experimental biology techniques. Given this network structure, the proposed inference algorithms make use of the expression data to predict the latent dynamics of transcription factor proteins. The thesis starts with an introductory chapter that familiarises the reader with the physical entities in biological systems; then we present the basic framework for inference in transcriptional regulation and highlight the main features of our approach. Then we introduce the methods and techniques that we use for inference in biological networks in chapter 2; it sets the foundation for the remaining chapters of the thesis. Chapter 3 describes four well-known methods for inference in transcriptional regulation with pros and cons of each method. Main contributions of the thesis are presented in the following three chapters. Chapter 4 describes a model for inference in transcriptional regulation using state space models. We extend this method to cope with the expression data obtained from multiple independent experiments where time dynamics are not present. We believe that the time has arrived to package methods like these into customised software packages tailored for biologists for analysing the expression data. So, we developed an open-sources, platform independent implementation of this method (TFInfer) that can process expression measurements with biological replicates to predict the activities of proteins and their influence on gene expression in gene regulatory network. The proteins in the regulatory network are known to interact with one another in regulating the expression of their downstream target genes. To take this into account, we propose a novel method to infer combinatorial effect of the proteins on gene expression using a variant of factorial hidden Markov model. We describe the inference mechanism in combinatorial factorial hidden model (cFHMM) using an efficient variational Bayesian expectation maximisation algorithm. We study the performance of the proposed model using simulated data analysis and identify its limitation in different noise conditions; then we use three real expression datasets to find the extent of combinatorial transcriptional regulation present in these datasets. This constitutes chapter 5 of the thesis. In chapter 6, we focus on problem of inferring the groups of proteins that are under the influence of same external signals and thus have similar effects on their downstream targets. Main objectives for this work are two fold: firstly, identifying the clusters of proteins with similar dynamics indicate their role is specific biological mechanisms and therefore potentially useful for novel biological insights; secondly, clustering naturally leads to better estimation of the transition rates of activity profiles of the regulatory proteins. The method we propose uses Dirichlet process mixtures to cluster the latent activity profiles of regulatory proteins that are modelled as latent Markov chain of a factorial hidden Markov model; we refer to this method as DPM-FHMM. We extensively test our methods using simulated and real datasets and show that our model shows better results for inference in transcriptional regulation compared to a standard factorial hidden Markov model. In the last chapter, we present conclusions about the work presented in this thesis and propose future directions for extending this work.
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Kang, Martin Hubert. "Post-transcriptional regulation of ABCA1". Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43655.

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Epidemiological studies consistently demonstrate an inverse relationship between HDL levels and cardiovascular disease (CVD), independent of LDL and triglyceride levels. Due to the crucial role ABCA1 plays in HDL biogenesis, increasing ABCA1 expression is considered an attractive strategy to increase plasma HDL levels. In this thesis we attempt to identify novel post-transcriptional and post-translational mechanisms that regulate ABCA1 expression and/or function. Prior to translation, ABCA1 protein expression is regulated by non-coding RNA molecules known as microRNAs which bind and inhibit translation of mature mRNA transcripts in the cytoplasm. In this study we used bioinformatic prediction programs to identify potential microRNA regulators of ABCA1. Using reporter constructs, protein expression analysis by immunoblotting, and cholesterol efflux assays, we validated microRNA-145 as a novel repressor of ABCA1 translation. The inhibition of endogenous microRNA-145 in HepG2 cells increases both ABCA1 protein levels and cholesterol efflux activity. The inhibition of this microRNA in the liver is a potential strategy to increase HDL levels. Following translation, numerous post-translational modifications and protein-protein interactions are required for the ABCA1 protein to function properly. In this study we identified palmitoylation as a novel post-translational modifier of ABCA1. The majority of ABCA1-mediated cholesterol efflux and HDL biogenesis occurs at the cell surface. We show that palmitoylation is a crucial lipid addition for proper ABCA1 plasma membrane localization. We also identify a number of enzymes that mediate the incorporation of radio-labeled palmitate onto ABCA1, and demonstrate that the overexpression of the palmitoyl transferase enzyme DHHC8 increases ABCA1 palmitoylation and cholesterol efflux activity. The increase of ABCA1 palmitoylation in the liver is a novel strategy to increase HDL levels. In this thesis, we have contributed to the understanding of ABCA1 biology by the identification of two novel regulators of ABCA1 expression and/or function.
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Glasspool, Rosalind M. "The transcriptional regulation of telomerase". Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398635.

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Weintraub, Abraham S. (Abraham Selby). "Transcriptional regulation and genome structure". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117886.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biology, 2018.
Cataloged from PDF version of thesis. Page 162 blink.
Includes bibliographical references.
The regulation of gene expression is fundamental to the control of cell identity, development and disease. The control of gene transcription is a major point in the regulation of gene expression. Transcription is regulated by the binding of transcription factors to DNA regulatory elements known as enhancers and promoters. This leads to the formation of a DNA loop connecting the enhancer and the promoter resulting in the subsequent transcription of the gene. Thus the structuring of the genome into DNA loops is important in the control of gene expression. This thesis will focus on the role of genome structure in transcriptional regulation. Two key questions in this area that I have attempted to address during my PhD are "how are enhancer-promoter interactions constrained so that enhancers do not operate nonspecifically?" and "are there proteins that facilitate enhancer-promoter looping?" I will describe the identification of DNA loop structures formed by CTCF and cohesin that constrain enhancer-promoter interactions. These structures-termed insulated neighborhoods-are perturbed in cancer and this perturbation results in the inappropriate activation of oncogenes. Additionally, I will describe the identification and characterization of the transcription factor YY1 as a factor that can structure enhancer-promoter loops. Through a combination of genetics, genomics, and biochemistry, my studies have helped to identify insulated neighborhood structures, shown the importance of these structures in the control of gene expression, revealed that these structures are mutated in cancer, and identified YY1 as a structural regulator of enhancer-promoter loops. I believe these studies have produced a deeper understanding of the regulatory mechanisms that connect the control of genome structure to the control of gene transcription.
by Abraham S. Weintraub.
Ph. D.
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McCormick, Margaret M. (Margaret Mary). "Transcriptional regulation in Corynebacterium glutamicum". Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/11197.

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Hochhauser, Daniel. "Transcriptional regulation of topoisomerase II". Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333178.

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Reid, John Edward. "Probabilistic models of transcriptional regulation". Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648864.

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Książki na temat "Transcriptional Regulation"

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L, McKnight Steven, i Yamamoto Keith R, red. Transcriptional regulation. Plainview, N.Y: Cold Spring Harbor Laboratory Press, 1992.

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Vancura, Ales, red. Transcriptional Regulation. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-61779-376-9.

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MUKHTAR, SHAHID, red. Modeling Transcriptional Regulation. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1534-8.

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Transcriptional regulation: Methods and protocols. New York: Humana Press, 2012.

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Dassi, Erik, red. Post-Transcriptional Gene Regulation. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-1851-6.

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Wilusz, Jeffrey, red. Post-Transcriptional Gene Regulation. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-033-1.

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Dassi, Erik, red. Post-Transcriptional Gene Regulation. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3067-8.

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Jeffrey, Wilusz, red. Post-transcriptional gene regulation. Totowa, N.J: Humana Press, 2008.

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Courey, Albert J. Mechanisms in transcriptional regulation. Malden, MA: Blackwell Pub., 2008.

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Wajapeyee, Narendra, i Romi Gupta, red. Eukaryotic Transcriptional and Post-Transcriptional Gene Expression Regulation. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6518-2.

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Części książek na temat "Transcriptional Regulation"

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Scotto, Kathleen W., i Tan A. Ince. "Transcriptional Regulation". W Basic Science of Cancer, 108–27. London: Current Medicine Group, 2000. http://dx.doi.org/10.1007/978-1-4684-8437-3_6.

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Huang, Yufei. "Transcriptional Regulation". W Encyclopedia of Systems Biology, 2253–54. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_815.

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Tuckermann, Jan, Peter Herrlich i Giorgio Caratti. "Transcriptional Regulation". W Encyclopedia of Molecular Pharmacology, 1–10. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-21573-6_255-1.

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Tuckermann, Jan, Peter Herrlich i Giorgio Caratti. "Transcriptional Regulation". W Encyclopedia of Molecular Pharmacology, 1504–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57401-7_255.

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Snyder, Lori A. S. "Transcriptional Regulation". W Bacterial Genetics and Genomics, 85–103. Wyd. 2. Boca Raton: Garland Science, 2024. http://dx.doi.org/10.1201/9781003380436-8.

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Moyano, Tomás C., Rodrigo A. Gutiérrez i José M. Alvarez. "Genomic Footprinting Analyses from DNase-seq Data to Construct Gene Regulatory Networks". W Modeling Transcriptional Regulation, 25–46. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1534-8_3.

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Aljedaani, Fatimah, Naganand Rayapuram i Ikram Blilou. "A Semi-In Vivo Transcriptional Assay to Dissect Plant Defense Regulatory Modules". W Modeling Transcriptional Regulation, 203–14. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1534-8_13.

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Wang, Xingwei, Yufeng Xu, Mian Zhou i Wei Wang. "Assessing Global Circadian Rhythm Through Single-Time-Point Transcriptomic Analysis". W Modeling Transcriptional Regulation, 215–25. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1534-8_14.

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AbuQamar, Synan F., Khaled A. El-Tarabily i Arjun Sham. "Co-expression Networks in Predicting Transcriptional Gene Regulation". W Modeling Transcriptional Regulation, 1–11. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1534-8_1.

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Muley, Vijaykumar Yogesh. "Mathematical Linear Programming to Model MicroRNAs-Mediated Gene Regulation Using Gurobi Optimizer". W Modeling Transcriptional Regulation, 287–301. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1534-8_19.

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Streszczenia konferencji na temat "Transcriptional Regulation"

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Pinard, Desre. "Eucalyptus grandis organellar gene transcriptional and post-transcriptional regulation in developing xylem". W ASPB PLANT BIOLOGY 2020. USA: ASPB, 2020. http://dx.doi.org/10.46678/pb.20.1053020.

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Ogul, Hasan, i Giray S. Ozcan. "A framework for integrative analysis of transcriptional and post-transcriptional gene regulation". W 2013 7th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2013. http://dx.doi.org/10.1109/icaict.2013.6722723.

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Canteiro, Beatriz, Maria Mendes, Filipa Jacques, Mariana Delgadinho, Ketlyn Oliveira, Catarina Ginete, Mário Gomes, Edna Ribeiro, Miguel Brito i Anita Gomes. "Effects of Quercetin in transcriptional and post-transcriptional regulation of fetal hemoglobin". W 2023 IEEE 7th Portuguese Meeting on Bioengineering (ENBENG). IEEE, 2023. http://dx.doi.org/10.1109/enbeng58165.2023.10175363.

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"Reconstruction of mathematical frame models of bacterial transcription regulation based on transcriptional regulatory networks". W Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-120.

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Krivosheev, Ivan, Lei Du i Xia Li. "Transcriptional Regulation of Human Gene Coexpression Network". W 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5163698.

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Giaretta, Alberto. "Noise in transcriptional, splicing and translational regulation". W 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2020. http://dx.doi.org/10.1109/cibcb48159.2020.9277724.

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Bolt, Tayah. "Transcriptional Regulation of the Plant Shikimate Pathway". W ASPB PLANT BIOLOGY 2020. USA: ASPB, 2020. http://dx.doi.org/10.46678/pb.20.1052617.

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"STRUCTURAL MOTIF ENUMERATION IN TRANSCRIPTIONAL REGULATION NETWORKS". W International Conference on Bioinformatics. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002760001870192.

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Yaglova, Nataliya Valentinovna, Sergey Stanislavovich Obernikhin, Valentin Vasilyevich Yaglov i Svetlana Vladimirovna Nazimova. "TRANSCRIPTIONAL REGULATION OF ADRENAL CORTEX POSTNATAL DEVELOPMENT AND FUNCTION". W International conference New technologies in medicine, biology, pharmacology and ecology (NT +M&Ec ' 2020). Institute of information technology, 2020. http://dx.doi.org/10.47501/978-5-6044060-0-7.08.

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Expression of transcriptional factor Oct4 and Shh in rat adrenal cortex during postnatal development and the role for this factors in functional activity of adrenal cortex and tissue homeostasis was determined.
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Rao, Arvind, Alfred Hero, David States i James Engel. "Manifold embedding for understanding mechanisms of transcriptional regulation". W 2006 IEEE International Workshop on Genomic Signal Processing and Statistics. IEEE, 2006. http://dx.doi.org/10.1109/gensips.2006.353127.

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Raporty organizacyjne na temat "Transcriptional Regulation"

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Thakur, Sanjay, i Carlo M. Croce. Transcriptional Regulation of BRCA1. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2001. http://dx.doi.org/10.21236/ada398226.

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Thakur, Sanjay, i Carlo Croce. Transcriptional Regulation of BRCA1. Fort Belvoir, VA: Defense Technical Information Center, sierpień 1999. http://dx.doi.org/10.21236/ada390711.

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Payne, Shannon R., i Mary C. King. Transcriptional Regulation of BRCA1. Fort Belvoir, VA: Defense Technical Information Center, październik 1999. http://dx.doi.org/10.21236/ada392036.

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Payne, Shannon R., i Mary C. King. Transcriptional regulation of BRCA1. Fort Belvoir, VA: Defense Technical Information Center, październik 2000. http://dx.doi.org/10.21236/ada392061.

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Couch, Fergus. Characterization of BRCA2 Transcriptional Regulation. Fort Belvoir, VA: Defense Technical Information Center, sierpień 1999. http://dx.doi.org/10.21236/ada382428.

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Rich, Alexander. Transcriptional Regulation in the Cell Cycle. Fort Belvoir, VA: Defense Technical Information Center, październik 1988. http://dx.doi.org/10.21236/ada200715.

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Rodenhiser, David I. Transcriptional Regulation and Targeting of NF1 Gene Expression. Fort Belvoir, VA: Defense Technical Information Center, październik 2001. http://dx.doi.org/10.21236/ada407208.

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Bredow, Sebastian. Transcriptional Regulation of VEGF Expression in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 2002. http://dx.doi.org/10.21236/ada407270.

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Bredow, Sebastian. Transcriptional Regulation of VEGF Expression in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 2004. http://dx.doi.org/10.21236/ada427135.

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Long-Sheng, Chang. Post Transcriptional Regulation of the Neurofibromatosis 2 Gene. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2004. http://dx.doi.org/10.21236/ada428293.

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