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Artykuły w czasopismach na temat "Prokaryotic Transcription"
Dixit, Vidula, Elisabetta Bini, Melissa Drozda i Paul Blum. "Mercury Inactivates Transcription and the Generalized Transcription Factor TFB in the Archaeon Sulfolobus solfataricus". Antimicrobial Agents and Chemotherapy 48, nr 6 (czerwiec 2004): 1993–99. http://dx.doi.org/10.1128/aac.48.6.1993-1999.2004.
Pełny tekst źródłaGoodrich, James A., i William R. McClure. "Competing promoters in prokaryotic transcription". Trends in Biochemical Sciences 16 (styczeń 1991): 394–97. http://dx.doi.org/10.1016/0968-0004(91)90162-o.
Pełny tekst źródłaPruss, Gail J., i Karl Drlica. "DNA supercoiling and prokaryotic transcription". Cell 56, nr 4 (luty 1989): 521–23. http://dx.doi.org/10.1016/0092-8674(89)90574-6.
Pełny tekst źródłaChávez, Joselyn, Damien P. Devos i Enrique Merino. "Complementary Tendencies in the Use of Regulatory Elements (Transcription Factors, Sigma Factors, and Riboswitches) in Bacteria and Archaea". Journal of Bacteriology 203, nr 2 (19.10.2020): e00413-20. http://dx.doi.org/10.1128/jb.00413-20.
Pełny tekst źródłaDecker, Katherine T., Ye Gao, Kevin Rychel, Tahani Al Bulushi, Siddharth M. Chauhan, Donghyuk Kim, Byung-Kwan Cho i Bernhard O. Palsson. "proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms". Nucleic Acids Research 50, nr D1 (17.11.2021): D1077—D1084. http://dx.doi.org/10.1093/nar/gkab1043.
Pełny tekst źródłaZheng, Ming, i Gisela Storz. "Redox sensing by prokaryotic transcription factors". Biochemical Pharmacology 59, nr 1 (styczeń 2000): 1–6. http://dx.doi.org/10.1016/s0006-2952(99)00289-0.
Pełny tekst źródłaHwang, Seungha, Jimin Lee i Jin Young Kang. "Prokaryotic transcription regulation by the nascent RNA elements". Korean Society for Structural Biology 8, nr 2 (30.06.2020): 33–40. http://dx.doi.org/10.34184/kssb.2020.8.2.33.
Pełny tekst źródłaJacques, J. P., i D. Kolakofsky. "Pseudo-templated transcription in prokaryotic and eukaryotic organisms." Genes & Development 5, nr 5 (1.05.1991): 707–13. http://dx.doi.org/10.1101/gad.5.5.707.
Pełny tekst źródłaChetal, Kashish, i Sarath Chandra Janga. "OperomeDB: A Database of Condition-Specific Transcription Units in Prokaryotic Genomes". BioMed Research International 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/318217.
Pełny tekst źródłaJones, Daniel L., Robert C. Brewster i Rob Phillips. "Promoter architecture dictates cell-to-cell variability in gene expression". Science 346, nr 6216 (18.12.2014): 1533–36. http://dx.doi.org/10.1126/science.1255301.
Pełny tekst źródłaRozprawy doktorskie na temat "Prokaryotic Transcription"
Martins, Leonardo Pedro Donas-Boto de Vilhena. "Stochastic model of transcription initiation of closely spaced promoters in escherichia coli". Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/7009.
Pełny tekst źródłaThe regulatory mechanisms of transcription allow organisms to quickly adapt to changes in their environment and often act during transcription initiation. Here, a stochastic model of transcription initiation at the nucleotide level is proposed to study the dynamics of RNA production in closely spaced promoters and their regulatory mechanisms. We study how different arrangements (convergent e divergent), distance between transcription start sites (TSS), and various kinetic parameters affect the dynamics of RNA production. Further, we analyze how the kinetics of various steps in transcription initiation can be regulated by varying locations of repressor binding sites. From the results, we observe that the rate limiting steps have strong influence in the kinetics of RNA production. We find that interferences between RNA polymerases in divergent overlapped and convergent geometries causes the distribution of time intervals between the production of consecutive RNA molecules from each TSS to increase in mean and standard deviation, which leads to stronger fluctuations in the temporal levels of RNA molecules. We observe that small changes in the distance between TSSs can lead to abrupt transitions in the dynamics of RNA production, particularly when this change changes the geometry from overlapped to non-overlapped promoters. From the study of the correlation in the choices of directionality and on the time series of RNA productions we show that by tuning the distances and directions of the two TSS one can obtain both negative and positive correlations. We further show that distinct repression mechanisms of transcription initiation in steps such as the open and closed complex formation and promoter escape have different effects on the dynamics of RNA production. The study of these models will help the study of how genetic circuits have evolved and assist in designing artificial genetic circuits with desired dynamics.
Bandekar, Aditya C. "Cell Cycle Associated Gene Expression Predicts Function in Mycobacteria". eScholarship@UMMS, 2020. https://escholarship.umassmed.edu/gsbs_diss/1068.
Pełny tekst źródłaDian, Cyril. "Adaptive Responses by Transcriptional Regulators to small molecules in Prokaryotes : Structural studies of two bacterial one-component signal transduction systems DntR and HpNikR". Doctoral thesis, Stockholm : Department of Biochemistry and Biophysics, Stockholm University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7052.
Pełny tekst źródłaElison, Kalman Grim. "Purification, functional characterization and crystallization of the PerR peroxide sensor from Saccharopolyspora erythraea". Thesis, Uppsala universitet, Strukturbiologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-387943.
Pełny tekst źródłaOtt, Alban. "Approches bioinformatiques pour identifier et caractériser les ARN régulateurs chez les procaryotes". Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112029.
Pełny tekst źródłaThe aim of this thesis was to improve our understanding of the RNA-dependent gene regulation in prokaryotes. Newly developed bioinformatics approaches revealed new non-coding regulatory RNAs and allowed us to identify putative targets.Regulatory RNAs can change the abundance of certain proteins by interacting with cognate messenger RNAs (mRNA). This effect is achieved through various modes of action that lead to the distinction of three RNA classes: small RNA (sRNA), cis-regulatory RNA (cisRNA) and antisense RNA (asRNA). With the generalization of experimental RNA identification (transcriptomics), it becomes easier to obtain the list of expressed RNA but most of their target mRNA remain unknown. Conversely, cisRNA cannot be easily identified through experimental procedures but their targets are obvious.To address these issues, we developed two new methods: the first predicts pairs of sRNA and mRNA targets based on the analysis of expression profiles and led us to propose a new regulatory network with sRNAs playing a central role in bacterial sporulation. The second identifies new RNAs in genomes based on the analysis of phylogenetic profiles. Our results suggest that the abundance of sRNAs and cisRNA were previously underestimated. We also suggest the presence of several cisRNAs in an Archaea, including a strong candidate of thermosensitive regulator.Progress made in this thesis contributed to a better understanding of RNA importance in bacterial cell regulation. Regulatory RNAs are abundant and present in more organisms than expected previously. These results are new evidences that the physiological roles of sRNAs are more central than was previously thought
Aditya, Kumar *. "Structural Feature of Prokaryotic Promoters and their Role in Gene Expression". Thesis, 2015. http://etd.iisc.ernet.in/2005/3528.
Pełny tekst źródłaChetal, Kashish. "OperomeDB: database of condition specific transcription in prokaryotic genomes and genomic insights of convergent transcription in bacterial genomes". Thesis, 2014. http://hdl.handle.net/1805/6228.
Pełny tekst źródłaMy thesis comprises of two individual projects: 1) we have developed a database for operon prediction using high-throughput sequencing datasets for bacterial genomes. 2) Genomics and mechanistic insights of convergent transcription in bacterial genomes. In the first project we developed a database for the prediction of operons for bacterial genomes using RNA-seq datasets, we predicted operons for bacterial genomes. RNA-seq datasets with different condition for each bacterial genome were taken into account and predicted operons using Rockhopper. We took RNA-seq datasets from NCBI with distinct experimental conditions for each bacterial genome into account and analyzed using tool for operon prediction. Currently our database contains 9 bacterial organisms for which we predicted operons. User interface is simple and easy to use, in terms of visualization, downloading and querying of data. In our database user can browse through reference genome, genes present in that genome and operons predicted from different RNA-seq datasets. Further in the second project, we studied the genomic and mechanistic insights of convergent transcription in bacterial genomes. We know that convergent gene pairs with overlapping head-to-head configuration are widely spread across both eukaryotic and prokaryotic genomes. They are believed to contribute to the regulation of genes at both transcriptional and post-transcriptional levels, although factors contributing to their abundance across genomes and mechanistic basis for their prevalence are poorly understood. In this study, we explore the role of various factors contributing to convergent overlapping transcription in bacterial genomes. Our analysis shows that the proportion of convergent overlapping gene pairs (COGPs) in a genome is affected due to endospore formation, bacterial habitat, oxygen requirement, GC content and the temperature range. In particular, we show that bacterial genomes thriving in specialized habitats, such as thermophiles, exhibit a high proportion of COGPs. Our results also conclude that the density distribution of COGPs across the genomes is high for shorter overlaps with increased conservation of distances for decreasing overlaps. Our study further reveals that COGPs frequently contain stop codon overlaps with the middle base position exhibiting mismatches between complementary strands. Further, for the functional analysis using cluster of orthologous groups (COGs) annotations suggested that cell motility, cell metabolism, storage and cell signaling are enriched among COGPs, suggesting their role in processes beyond regulation. Our analysis provides genomic insights into this unappreciated regulatory phenomenon, allowing a refined understanding of their contribution to bacterial phenotypes.
Vogel, Sabine Katja [Verfasser]. "Mechanistic studies on transcription activation via DNA looping in a prokaryotic promoter-enhancer system / presented by Sabine Katja Vogel". 2004. http://d-nb.info/972519467/34.
Pełny tekst źródłaLyubetskaya, Anna. "Transcription factor binding distribution and properties in prokaryotes". Thesis, 2015. https://hdl.handle.net/2144/15425.
Pełny tekst źródłaWu, Fu-Rong, i 吳阜融. "Uncovering the Bursting Phenomenon of Gene Transcription in Prokaryotes". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/90869861888122197099.
Pełny tekst źródła國立臺灣大學
電子工程學研究所
100
Gene expression consists of two main steps: transcription and translation. It origins from the binding of RNA polymerases to their target sites on DNA sequences. The mechanism how RNA polymerases locate their target sites remains a puzzling mystery. It affects almost all aspects of biology. Over the past few decades, many related studies have been made on the regulation of gene expression. Although several models have been proposed and demonstrated for the mechanism, many details of the elementary steps of gene transcription in vivo are still open for debate. This thesis aims to explain how the motion of RNA polymerases affects gene transcription dynamics and the transcriptional bursting. We introduce a random walk model for the motion of RNA polymerases along DNA during the search of target locations and the transcription process. In order to verify our model, we apply Monte Carlo simulation and simplified statistical computation to compare our prediction to prior experimental data. The findings suggest that under proper assumptions, our model is able to explain the transcriptional bursting phenomenon, and computer simulations are consistent with prior experimental data. Our results also suggest some parameters which await experiments to justify their biological significances.
Książki na temat "Prokaryotic Transcription"
Transcription Regulation in Prokaryotes. Oxford University Press, USA, 2000.
Znajdź pełny tekst źródłaKirchman, David L. Genomes and meta-omics for microbes. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789406.003.0005.
Pełny tekst źródłaCzęści książek na temat "Prokaryotic Transcription"
Sybers, David, Daniel Charlier i Eveline Peeters. "In Vitro Transcription Assay for Archaea Belonging to Sulfolobales". W Prokaryotic Gene Regulation, 81–102. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2413-5_6.
Pełny tekst źródłaSeshasayee, Aswin Sai Narain, Karthikeyan Sivaraman i Nicholas M. Luscombe. "An Overview of Prokaryotic Transcription Factors". W Subcellular Biochemistry, 7–23. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9069-0_2.
Pełny tekst źródłaLedesma, Leonardo, Rafael Hernandez-Guerrero i Ernesto Perez-Rueda. "Prediction of DNA-Binding Transcription Factors in Bacteria and Archaea Genomes". W Prokaryotic Gene Regulation, 103–12. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2413-5_7.
Pełny tekst źródłaHilchey, S., J. Xu i G. B. Koudelka. "Indirect Effects of DNA Sequence on Transcriptional Activation by Prokaryotic DNA Binding Proteins". W Mechanisms of Transcription, 115–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60691-5_9.
Pełny tekst źródłaBernauw, Amber Joka, Veerke De Kock i Indra Bervoets. "In Vivo Screening Method for the Identification and Characterization of Prokaryotic, Metabolite-Responsive Transcription Factors". W Prokaryotic Gene Regulation, 113–41. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2413-5_8.
Pełny tekst źródłaBuc, H. "Initiation of Prokaryotic Transcription-Kinetic and Structural Approaches". W Nucleic Acids and Molecular Biology, 186–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-46596-3_11.
Pełny tekst źródłaKigawa, Takanori. "Cell-Free Protein Preparation Through Prokaryotic Transcription–Translation Methods". W Methods in Molecular Biology, 1–10. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-331-2_1.
Pełny tekst źródłaOehler, Stefan, i Benno Müller-Hill. "Prokaryotic control of transcription: How and why does it differ from eukaryotic control?" W Inducible Gene Expression, Volume 1, 1–24. Boston, MA: Birkhäuser Boston, 1995. http://dx.doi.org/10.1007/978-1-4684-6840-3_1.
Pełny tekst źródłaLaub, Michael T., i R. Frank Rosenzweig. "Transcriptional Profiling in Bacteria Using Microarrays". W Prokaryotic Genomics, 131–44. Basel: Birkhäuser Basel, 2003. http://dx.doi.org/10.1007/978-3-0348-8963-6_11.
Pełny tekst źródłaGeorg, Jens, i Wolfgang R. Hess. "Widespread Antisense Transcription in Prokaryotes". W Regulating with RNA in Bacteria and Archaea, 191–210. Washington, DC, USA: ASM Press, 2018. http://dx.doi.org/10.1128/9781683670247.ch12.
Pełny tekst źródłaStreszczenia konferencji na temat "Prokaryotic Transcription"
Ni, Chung-En, Duy-Phuong Doan, Yen-Jung Chiu i Yen-Hua Huang. "TSSNet – A Deep Neural Network Model for Predicting Prokaryotic Transcription Start Sites". W 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2022. http://dx.doi.org/10.1109/bibe55377.2022.00054.
Pełny tekst źródłaPolstein, Lauren R., i Charles A. Gersbach. "Photoregulated Gene Expression in Human Cells With Light-Inducible Engineered Transcription Factors". W ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80573.
Pełny tekst źródłaRaporty organizacyjne na temat "Prokaryotic Transcription"
Schuster, Gadi, i David Stern. Integrated Studies of Chloroplast Ribonucleases. United States Department of Agriculture, wrzesień 2011. http://dx.doi.org/10.32747/2011.7697125.bard.
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