Academic literature on the topic 'Promoter Recognition'
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Journal articles on the topic "Promoter Recognition"
Fickett, James W., and Artemis G. Hatzigeorgiou. "Eukaryotic Promoter Recognition." Genome Research 7, no. 9 (September 1, 1997): 861–78. http://dx.doi.org/10.1101/gr.7.9.861.
Full textMao, Steve. "Mechanism of promoter recognition." Science 362, no. 6421 (December 20, 2018): 1372.11–1374. http://dx.doi.org/10.1126/science.362.6421.1372-k.
Full textShen, Li, Xiaogeng Feng, Yuan Yuan, Xudong Luo, Thomas P. Hatch, Kelly T. Hughes, Jun S. Liu, and You-xun Zhang. "Selective Promoter Recognition by Chlamydial σ28 Holoenzyme." Journal of Bacteriology 188, no. 21 (August 25, 2006): 7364–77. http://dx.doi.org/10.1128/jb.01014-06.
Full textBajic, V. B., S. H. Seah, A. Chong, G. Zhang, J. L. Y. Koh, and V. Brusic. "Dragon Promoter Finder: recognition of vertebrate RNA polymerase II promoters." Bioinformatics 18, no. 1 (January 1, 2002): 198–99. http://dx.doi.org/10.1093/bioinformatics/18.1.198.
Full textBUSBY, S. "Promoter structure, promoter recognition, and transcription activation in prokaryotes." Cell 79, no. 5 (December 1994): 743–46. http://dx.doi.org/10.1016/0092-8674(94)90063-9.
Full textBrunner, M., and H. Bujard. "Promoter recognition and promoter strength in the Escherichia coli system." EMBO Journal 6, no. 10 (October 1987): 3139–44. http://dx.doi.org/10.1002/j.1460-2075.1987.tb02624.x.
Full textDeng, Wensheng, Barbora Malecová, Thomas Oelgeschläger, and Stefan G. E. Roberts. "TFIIB Recognition Elements Control the TFIIA-NC2 Axis in Transcriptional Regulation." Molecular and Cellular Biology 29, no. 6 (December 29, 2008): 1389–400. http://dx.doi.org/10.1128/mcb.01346-08.
Full textHutchinson, Gordon. "International workshop tackles promoter recognition problem." Trends in Genetics 12, no. 4 (April 1996): 159. http://dx.doi.org/10.1016/0168-9525(96)30021-8.
Full textLukashin, A. V., V. V. Anshelevich, B. R. Amirikyan, A. I. Gragerov, and M. D. Frank-Kamenetskii. "Neural Network Models for Promoter Recognition." Journal of Biomolecular Structure and Dynamics 6, no. 6 (June 1989): 1123–33. http://dx.doi.org/10.1080/07391102.1989.10506540.
Full textWang, Lei, Yuli Guo, and Jay D. Gralla. "Regulation of Sigma 54-Dependent Transcription by Core Promoter Sequences: Role of −12 Region Nucleotides." Journal of Bacteriology 181, no. 24 (December 15, 1999): 7558–65. http://dx.doi.org/10.1128/jb.181.24.7558-7565.1999.
Full textDissertations / Theses on the topic "Promoter Recognition"
Li, Xiaomeng. "Human Promoter Recognition Based on Principal Component Analysis." Thesis, The University of Sydney, 2008. http://hdl.handle.net/2123/3656.
Full textLi, Xiaomeng. "Human Promoter Recognition Based on Principal Component Analysis." University of Sydney, 2008. http://hdl.handle.net/2123/3656.
Full textThis thesis presents an innovative human promoter recognition model HPR-PCA. Principal component analysis (PCA) is applied on context feature selection DNA sequences and the prediction network is built with the artificial neural network (ANN). A thorough literature review of all the relevant topics in the promoter prediction field is also provided. As the main technique of HPR-PCA, the application of PCA on feature selection is firstly developed. In order to find informative and discriminative features for effective classification, PCA is applied on the different n-mer promoter and exon combined frequency matrices, and principal components (PCs) of each matrix are generated to construct the new feature space. ANN built classifiers are used to test the discriminability of each feature space. Finally, the 3 and 5-mer feature matrix is selected as the context feature in this model. Two proposed schemes of HPR-PCA model are discussed and the implementations of sub-modules in each scheme are introduced. The context features selected by PCA are III used to build three promoter and non-promoter classifiers. CpG-island modules are embedded into models in different ways. In the comparison, Scheme I obtains better prediction results on two test sets so it is adopted as the model for HPR-PCA for further evaluation. Three existing promoter prediction systems are used to compare to HPR-PCA on three test sets including the chromosome 22 sequence. The performance of HPR-PCA is outstanding compared to the other four systems.
Pieretti, Simone. "ToxT promoter recognition by ToxR transcription factor, a co-activator within the Vibrio cholerae virulence cascade." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/396666.
Full textEl cólera es una infección diarreica aguda causada por la bacteria Vibrio cholerae. La producción de la toxina colérica se controla a través del regulador maestro de virulencia ToxT, cuya activación se lleva a cabo por las proteínas de membrana ToxR y TcpP. Este proyecto de tesis tiene como objetivo el estudio de los complejos formados por ToxR junto con el ADN, dado que se conoce que ToxR se une al promotor toxT para reclutar TcpP y consecuentemente la ARN polimerasa, produciendo la activación de la transcripción. Mediante cristalografía de rayos X hemos resuelto la estructura de tres complejos del dominio de unión a ADN de ToxR con oligonucleótidos de 20, 40 y 25 pares de bases a resoluciones de 2.0 A, 2.6 A y 3.2 A, respectivamente. De acuerdo con las tres estructuras, ToxR es capaz de unirse a una amplia región del promotor toxT que se expande desde la posición -97 hasta la posición -45. Teniendo en cuenta el modelo integrado de las tres estructuras, cuatro moléculas de ToxR se unen al promotor toxT en tándem e invertidas. En las tres estructuras, ToxR muestra un tipo de plegamiento winged helix-turn-helix (w-HTH). El ala (wing) interactúa con el surco menor del ADN, mientras que la hélice de reconocimiento penetra en el surco mayor. Comparando ToxR con el resto de proteínas de la familia w-HTH, hemos encontrado un nuevo elemento estructural, el ala secundaria (secondary wing), que interacciona con el ADN. La determinación de la estructura de los tres complejos es importante para definir con mayor precisión el sitio de unión de ToxR en el promotor toxT. Este sitio se caracteriza por once bases con una secuencia rica en A-T seguida de una caja CATA/CATG/TGTA, donde las dos últimas bases contactan directamente y específicamente con la proteína. Proponemos que ToxR actuaría como co-activador de la transcripción de toxT a diferentes niveles: (i) podría ser responsable de capturar el ADN y mantenerlo cerca de la membrana citoplasmática, (ii) podría jugar un papel clave en el desplazamiento de H-NS, (iii) podría reclutar TcpP y estabilizar su interacción con el promotor.
Sanderson, Andrew. "Recognition of 'extended-10' elements of bacterial promoters." Thesis, University of Birmingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275668.
Full textZhang, Da Jiang. "Involvement of the Polypyrimidine Tract-Binding Protein-Associated Splicing Factor (PSF) in the Hepatitis Delta Virus (HDV) RNA-Templated Transcription." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31095.
Full textMiroslavova, Nora Svetoslavova. "Studies on the recognition of Escherichia coli promoters and their elements." Thesis, University of Birmingham, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.422293.
Full textUgolini, Matteo. "Recognition of microbial viability via TLR8 promotes innate and adaptive immunity." Doctoral thesis, Humboldt-Universität zu Berlin, 2019. http://dx.doi.org/10.18452/20035.
Full textThe detection of the so-called vitality-associated molecular patterns (vita-PAMPs) signals to the immune system the presence of living microorganisms and triggers an increased immune response. The present study investigated the detection of bacterial vitality by human antigen-presenting cells (APC), as well as the effects of this recognition events on adaptive immunity. Transcriptome analysis of human monocytes showed a selective transcriptional response to live versus heat-killed bacteria. Among others, the inflammatory cytokines IL-12 and TNF were expressed almost exclusively in response to live bacteria. Moreover, the detection of bacterial vitality is conserved in humans, pigs, mice and fish. In mice, bacterial RNA was identified as a bacterial vita-PAMP. In human monocytes, supplementation of dead bacteria with bacterial RNA or with synthetic ligands of toll-like receptor (TLR) 7 and TLR8, but not with other TLR ligands, resulted in the reconstitution of the TNF and IL-12 responses. Conversely, silencing of TLR8 inhibited vita-PAMP-dependent cytokine production. T-follicular helper cells (TFH) play a central role in the initiation of humoral immune responses. Here, the recognition of living bacteria, bacterial RNA or synthetic TLR8 ligands by APCs was identified as a stimulus for robust TFH cell differentiation. TFH differentiation is dependent on the recognition of bacterial RNA via TLR8 and the production of IL-12. Immunization of pigs with a live bacterial vaccine elicited significantly more robust TFH cell and antibody responses than immunization with the heat-killed version of the same vaccine. In summary, we identified TLR8 as the first known vita-PAMP receptor in human and demonstrated its pivotal role in TLR8-mediated “viability recognition” for the induction of TFH cells and vaccine reactions.
Hedemalm, Emil. "Online Transportation Mode Recognition and an Application to Promote Greener Transportation." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65348.
Full textDel av Erasmus Mundus PERCCOM. Redovisning skedde på anordnad summer school av partner-universitet där hela konsortiet närvarade.
Keselowsky, Benjamin George. "Engineering surgaces to direct integrin binding and signaling to promote osteoblast differentiation." Available online, Georgia Institute of Technology, 2004, 2004. http://etd.gatech.edu/theses/available/etd-03152004-111413/.
Full textDavid Collard, Committee Member ; Robert Guldberg, Committee Member ; Cheng Zhu, Committee Member ; Elliot Chaikoff, Committee Member ; Harish Radhakrishna, Committee Member ; Andres J. Garcia, Committee Chair. Includes bibliographical references.
Brown, Maria D. "Does Retrieval Practice Among Medical Trainees Promote Recognition, Diagnosis and Treatment of Eating Disorders?" The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606914020488199.
Full textBooks on the topic "Promoter Recognition"
Sanderson, Andrew. Recognition of 'extended-10' elements of bacterial promoters. Birmingham: University of Birmingham, 2003.
Find full textBurr, Tom. Recognition of 'extended-10' promoters by RNA polymerase. Birmingham: University of Birmingham, 2000.
Find full textGlucksmann, Maria Alexandra. Determinants of N4 virion RNA polymerase-promoter recognition. 1989.
Find full textDiversity, Violence, and Recognition: How Recognizing Ethnic Identity Promotes Peace. Oxford University Press, Incorporated, 2020.
Find full textSamii, Cyrus, and Elisabeth King. Diversity, Violence, and Recognition: How Recognizing Ethnic Identity Promotes Peace. Oxford University Press, Incorporated, 2020.
Find full textReader, Jocelyn, Sarah Lynam, Amy Harper, Gautam Rao, Maya Matheny, and Dana M. Roque. Ovarian Tumor Microenvironment and Innate Immune Recognition. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190248208.003.0004.
Full textKistler, S. Ashley. Recognition and Immortality in the Market and Beyond. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252038358.003.0004.
Full textFrost & Sullivan., ed. U.S. electronic access control system markets: High security requirements promote biometric identification. Mountain View, CA: Frost & Sullivan, 1994.
Find full textJungbluth, Konstanze, Mônica Savedra, and Rita Vallentin, eds. Language – Belonging – Politics. Nomos Verlagsgesellschaft mbH & Co. KG, 2022. http://dx.doi.org/10.5771/9783748911548.
Full textJan, McArthur, and Napier University, eds. PROMOTE: Professional Recognition of Methods of Promoting Teaching and Learning Enhancement : alternative ways of fostering educational development in higher education. Edinburgh: Napier University, 2004.
Find full textBook chapters on the topic "Promoter Recognition"
Rani, T. Sobha, S. Durga Bhavani, and S. Bapi Raju. "Promoter Recognition Using Neural Network Approaches." In Computational Intelligence and Pattern Analysis in Biological Informatics, 71–97. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470872352.ch4.
Full textBajić, Vladimir B., and Ivan V. Bajić. "Neural Network System for Promoter Recognition." In Future Directions for Intelligent Systems and Information Sciences, 288–305. Heidelberg: Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1856-7_14.
Full textYang, Xinyi, and Annalisa Marsico. "In Silico Promoter Recognition from deepCAGE Data." In Methods in Molecular Biology, 171–99. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-4035-6_13.
Full textLangroudi, Seyyed Mohammad Shaheri, Hamid Reza Hamidi, and Shokooh Kermanshahani. "A Parallel Algorithm for Eukaryotic Promoter Recognition." In Communications in Computer and Information Science, 468–75. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33495-6_36.
Full textConilione, Paul C., and Dianhui Wang. "E-Coli Promoter Recognition Using Neural Networks with Feature Selection." In Lecture Notes in Computer Science, 61–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11538356_7.
Full textTinnungwattana, Orawan, and Chidchanok Lursinsap. "Statistical Feature Selection from Chaos Game Representation for Promoter Recognition." In Computational Science – ICCS 2006, 838–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758525_112.
Full textGordon, Leo, Alexey Ya Chervonenkis, Alex J. Gammerman, Ilham A. Shahmuradov, and Victor V. Solovyev. "Genome-Wide Prokaryotic Promoter Recognition Based on Sequence Alignment Kernel." In Advances in Intelligent Data Analysis V, 386–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45231-7_36.
Full textXu, Wenxuan, Wenzheng Bao, Lin Yuan, and ZhiChao Jiang. "DSD-SVMs: Human Promoter Recognition Based on Multiple Deep Divergence Features." In Intelligent Computing Theories and Application, 515–26. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63309-1_46.
Full textBusby, Stephen, Annie Kolb, and Henri Buc. "Where it all Begins: An Overview of Promoter Recognition and Open Complex Formation." In RNA Polymerases as Molecular Motors, 13–37. Cambridge: Royal Society of Chemistry, 2009. http://dx.doi.org/10.1039/9781847559982-00013.
Full textWijffelman, Carel, Bas Zaat, Herman Spaink, Ine Mulders, Ton van Brussel, Rob Okker, Elly Pees, Ruud de Maagd, and Ben Lugtenberg. "Induction of Rhizobium Nod Genes by Flavonoids: Differential Adaptation of Promoter, nodD Gene and Inducers for Various Cross-Inoculation Groups." In Recognition in Microbe-Plant Symbiotic and Pathogenic Interactions, 123–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71652-2_12.
Full textConference papers on the topic "Promoter Recognition"
Zeng, Jia, Xiao-Qin Cao, and Hong Yan. "Human Promoter Recognition using Kullback-Leibler Divergence." In 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370721.
Full textTao, Lan, Ning Fan, and Zexuan Zhu. "A hybrid evolutionary algorithm for promoter recognition." In 2012 5th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2012. http://dx.doi.org/10.1109/bmei.2012.6512883.
Full textByeon, B., and K. Rasheed. "Bayesian Networks and Genetic Algorithms for Promoter Recognition." In IASTED Technology Conferences 2010. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.728-030.
Full textGuzman-Ruiz, Omar, Manuel Mejia-Lavalle, Alicia Martinez, and Yasmin Hernandez. "Machine learning Algorithms applied to Genetic Promoter Sequences Recognition." In 2020 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE). IEEE, 2020. http://dx.doi.org/10.1109/icmeae51770.2020.00016.
Full textQian, Ying, Yu Zhang, Bingyu Guo, Shasha Ye, Yuzhu Wu, and Jiongmin Zhang. "An Improved Promoter Recognition Model Using Convolutional Neural Network." In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2018. http://dx.doi.org/10.1109/compsac.2018.00072.
Full textTao, Lan, Huakui Chen, Yanmeng Xu, and Zexuan Zhu. "A New Promoter Recognition Method Based on Features Optimal Selection." In 2011 5th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2011. http://dx.doi.org/10.1109/icbbe.2011.5779973.
Full textShuo, Guo, Yuan De-cheng, Guo Wa, Zhang Bochen, and Li Jin-na. "Recognition of human promoter based on GMM and rough set." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8027653.
Full textRani, T. Sobha, S. Durga Bhavani, and Raju S. Bapi. "Promoter Recognition using dinucleotide Features : A Case Study for E.Coli." In 9th International Conference on Information Technology (ICIT'06). IEEE, 2006. http://dx.doi.org/10.1109/icit.2006.75.
Full textKamath, Uday, Kenneth A. De Jong, and Amarda Shehu. "An evolutionary-based approach for feature generation: Eukaryotic promoter recognition." In 2011 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2011. http://dx.doi.org/10.1109/cec.2011.5949629.
Full textBASHFORD, J. D. "INVESTIGATING ROLES OF DNA FLEXIBILITY IN PROMOTER RECOGNITION AND REGULATION." In Proceedings of the 3rd Annual RECOMB Workshop. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2008. http://dx.doi.org/10.1142/9781848162525_0021.
Full textReports on the topic "Promoter Recognition"
Iffat, Idris. Best Practices in CRSV Monitoring and Early Warning. Institute of Development Studies, June 2022. http://dx.doi.org/10.19088/k4d.2022.126.
Full textHall, Mark, and Neil Price. Medieval Scotland: A Future for its Past. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.165.
Full textGreenhill, Lucy, Christopher Leakey, and Daniela Diz. Second Workshop report: Mobilising the science community in progessing towards a sustainable and inclusive ocean economy. Scottish Universities Insight Institute, July 2021. http://dx.doi.org/10.15664/10023.23693.
Full textYaari, Menahem, Elhanan Helpman, Ariel Weiss, Nathan Sussman, Ori Heffetz, Hadas Mandel, Avner Offer, et al. Sustainable Well-Being in Israel. The Israel Academy of Sciences and Humanities, June 2021. http://dx.doi.org/10.52873/policy.2021.wellbeing-en.
Full textHenderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Southern Plains Inventory & Monitoring Network. National Park Service, June 2022. http://dx.doi.org/10.36967/nrr-2293756.
Full textElmann, Anat, Orly Lazarov, Joel Kashman, and Rivka Ofir. therapeutic potential of a desert plant and its active compounds for Alzheimer's Disease. United States Department of Agriculture, March 2015. http://dx.doi.org/10.32747/2015.7597913.bard.
Full textHenderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Sonoran Desert Inventory & Monitoring Network. National Park Service, September 2022. http://dx.doi.org/10.36967/2294374.
Full textPotts, Tavis, and Rebecca Ford. Leading from the front? Increasing Community Participation in a Just Transition to Net Zero in the North-East of Scotland. Scottish Universities Insight Institute, December 2022. http://dx.doi.org/10.57064/2164/19722.
Full textSaville, Alan, and Caroline Wickham-Jones, eds. Palaeolithic and Mesolithic Scotland : Scottish Archaeological Research Framework Panel Report. Society for Antiquaries of Scotland, June 2012. http://dx.doi.org/10.9750/scarf.06.2012.163.
Full textHenderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: National Capital Region Inventory & Monitoring Network. National Park Service, July 2022. http://dx.doi.org/10.36967/2293865.
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