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Relevant bibliographies by topics / Structure de motifs

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Academic literature on the topic 'Structure de motifs'

Author: Grafiati

Published: 10 June 2023

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Journal articles on the topic "Structure de motifs"

1

Han, Jiahui, Shijie Jiang, Zhengfu Zhou, Min Lin, and Jin Wang. "Artificial Proteins Designed from G3LEA Contribute to Enhancement of Oxidation Tolerance in E. coli in a Chaperone-like Manner." Antioxidants 12, no. 6 (2023): 1147. http://dx.doi.org/10.3390/antiox12061147.

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G3LEA is a family of proteins that exhibit chaperone-like activity when under distinct stress. In previous research, DosH was identified as a G3LEA protein from model extremophile—Deinococcus radiodurans R1 with a crucial core HD domain consisting of eight 11-mer motifs. However, the roles of motifs participating in the process of resistance to stress and their underlying mechanisms remain unclear. Here, eight different proteins with tandem repeats of the same motif were synthesized, named Motif1–8, respectively, whose function and structure were discussed. In this way, the role of each motif

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Badr, Ghada, Isra Al-Turaiki, Marcel Turcotte, and Hassan Mathkour. "IncMD: Incremental trie-based structural motif discovery algorithm." Journal of Bioinformatics and Computational Biology 12, no. 05 (2014): 1450027. http://dx.doi.org/10.1142/s0219720014500279.

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The discovery of common RNA secondary structure motifs is an important problem in bioinformatics. The presence of such motifs is usually associated with key biological functions. However, the identification of structural motifs is far from easy. Unlike motifs in sequences, which have conserved bases, structural motifs have common structure arrangements even if the underlying sequences are different. Over the past few years, hundreds of algorithms have been published for the discovery of sequential motifs, while less work has been done for the structural motifs case. Current structural motif di

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Leontis, Neocles B., and Eric Westhof. "The Annotation of RNA Motifs." Comparative and Functional Genomics 3, no. 6 (2002): 518–24. http://dx.doi.org/10.1002/cfg.213.

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The recent deluge of new RNA structures, including complete atomic-resolution views of both subunits of the ribosome, has on the one hand literally overwhelmed our individual abilities to comprehend the diversity of RNA structure, and on the other hand presented us with new opportunities for comprehensive use of RNA sequences for comparative genetic, evolutionary and phylogenetic studies. Two concepts are key to understanding RNA structure: hierarchical organization of global structure and isostericity of local interactions. Global structure changes extremely slowly, as it relies on conserved

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Shamim, Amen, Maria Razzaq, and Kyeong Kyu Kim. "MD-TSPC4: Computational Method for Predicting the Thermal Stability of I-Motif." International Journal of Molecular Sciences 22, no. 1 (2020): 61. http://dx.doi.org/10.3390/ijms22010061.

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I-Motif is a tetrameric cytosine-rich DNA structure with hemi-protonated cytosine: cytosine base pairs. Recent evidence showed that i-motif structures in human cells play regulatory roles in the genome. Therefore, characterization of novel i-motifs and investigation of their functional implication are urgently needed for comprehensive understanding of their roles in gene regulation. However, considering the complications of experimental investigation of i-motifs and the large number of putative i-motifs in the genome, development of an in silico tool for the characterization of i-motifs in the

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Alam, Tanvir, Meshari Alazmi, Xin Gao, and Stefan T. Arold. "How to find a leucine in a haystack? Structure, ligand recognition and regulation of leucine–aspartic acid (LD) motifs." Biochemical Journal 460, no. 3 (2014): 317–29. http://dx.doi.org/10.1042/bj20140298.

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LD motifs (leucine–aspartic acid motifs) are short helical protein–protein interaction motifs that have emerged as key players in connecting cell adhesion with cell motility and survival. LD motifs are required for embryogenesis, wound healing and the evolution of multicellularity. LD motifs also play roles in disease, such as in cancer metastasis or viral infection. First described in the paxillin family of scaffolding proteins, LD motifs and similar acidic LXXLL interaction motifs have been discovered in several other proteins, whereas 16 proteins have been reported to contain LDBDs (LD moti

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Tran, Ngoc Tam L., Luke DeLuccia, Aidan F. McDonald, and Chun-Hsi Huang. "Cross-Disciplinary Detection and Analysis of Network Motifs." Bioinformatics and Biology Insights 9 (January 2015): BBI.S23619. http://dx.doi.org/10.4137/bbi.s23619.

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The detection of network motifs has recently become an important part of network analysis across all disciplines. In this work, we detected and analyzed network motifs from undirected and directed networks of several different disciplines, including biological network, social network, ecological network, as well as other networks such as airlines, power grid, and co-purchase of political books networks. Our analysis revealed that undirected networks are similar at the basic three and four nodes, while the analysis of directed networks revealed the distinction between networks of different disc

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Banjade, Huta R., Sandro Hauri, Shanshan Zhang, et al. "Structure motif–centric learning framework for inorganic crystalline systems." Science Advances 7, no. 17 (2021): eabf1754. http://dx.doi.org/10.1126/sciadv.abf1754.

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Incorporation of physical principles in a machine learning (ML) architecture is a fundamental step toward the continued development of artificial intelligence for inorganic materials. As inspired by the Pauling’s rule, we propose that structure motifs in inorganic crystals can serve as a central input to a machine learning framework. We demonstrated that the presence of structure motifs and their connections in a large set of crystalline compounds can be converted into unique vector representations using an unsupervised learning algorithm. To demonstrate the use of structure motif information,

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Al-Khafaji, Hussein, and Ghada Kassim. "A New Approach to Motif Templates Analysis via Compilation Technique." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 2 (October 15, 2021): 180–208. http://dx.doi.org/10.55562/jrucs.v34i2.289.

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Motif template assertion and analysis is compulsory operation in most of bioinformatics systems such as motif search, sequential pattern miner, and bioinformatics databases analysis. The motif template can be in any length, therefore, the typing errors increased according to the length of motif. Also, when the structure motifs are submitted to bioinformatics systems they require specification of their components, i.e. the simple motifs, gaps, and the limits of the gaps. This research proposed a context free grammar, GFC, to describe the motif structure, and then this CFG is utilized to design

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Buckett, M. I., L. D. Marks, and D. E. Luzzi. "Correlation analysis of structure images." Proceedings, annual meeting, Electron Microscopy Society of America 45 (August 1987): 752–53. http://dx.doi.org/10.1017/s0424820100128079.

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A typical high resolution structure image contains a large amount of intensity information which is masked by both statistical and amorphous noise. One useful method of quantifying such images is to employ correlation techniques. When one seeks to quantify the atom column positions, correlation techniques can be used to decompose the image into separate motifs (of specific peak amplitudes and positions - each motif corresponding to a single column of atoms), thereby reducing the data to a more manageable form.This problem can be considered as the least squares minimization of the function: whe

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XING, ERIC P., WEI WU, MICHAEL I. JORDAN, and RICHARD M. KARP. "LOGOS: A MODULAR BAYESIAN MODEL FOR DE NOVO MOTIF DETECTION." Journal of Bioinformatics and Computational Biology 02, no. 01 (2004): 127–54. http://dx.doi.org/10.1142/s0219720004000508.

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The complexity of the global organization and internal structure of motifs in higher eukaryotic organisms raises significant challenges for motif detection techniques. To achieve successful de novo motif detection, it is necessary to model the complex dependencies within and among motifs and to incorporate biological prior knowledge. In this paper, we present LOGOS, an integrated LOcal and GlObal motif Sequence model for biopolymer sequences, which provides a principled framework for developing, modularizing, extending and computing expressive motif models for complex biopolymer sequence analy

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Dissertations / Theses on the topic "Structure de motifs"

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Tang, Thomas Cheuk Kai. "Discovering Protein Sequence-Structure Motifs and Two Applications to Structural Prediction." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1188.

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This thesis investigates the correlations between short protein peptide sequences and local tertiary structures. In particular, it introduces a novel algorithm for partitioning short protein segments into clusters of local sequence-structure motifs, and demonstrates that these motif clusters contain useful structural information via two applications to structural prediction. The first application utilizes motif clusters to predict local protein tertiary structures. A novel dynamic programming algorithm that performs comparably with some of the best existing algorithms is describe

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Stombaugh, Jesse. "Predicting the Structure of RNA 3D Motifs." Bowling Green State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1225391806.

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Gaillard, Anne-Laure. "Identification de motifs au sein des structures biologiques arborescentes." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2011. http://tel.archives-ouvertes.fr/tel-00652227.

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Avec l'explosion de la quantité de données biologiques disponible, développer de nouvelles méthodes de traitements efficaces est une problématique majeure en bioinformatique. De nombreuses structures biologiques sont modélisées par des structures arborescentes telles que les structures secondaires d'ARN et l'architecture des plantes. Ces structures contiennent des motifs répétés au sein même de leur structure mais également d'une structure à l'autre. Nous proposons d'exploiter cette propriété fondamentale afin d'améliorer le stockage et le traitement de tels objets. En nous inspirant du princi

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Dyer, Charlotte Emma. "Investigation of the structure of fibrillin eight-cysteine motifs." Thesis, University of Manchester, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488146.

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The eight-cysteine motif is a protein repeat sequence that has been identified in extracellular matrix proteins of the fibrillin superfamily which includes isoforms fibrillin-l and fibrillin-2 and the closely related latent transforming growth factor-B binding proteins (LTBPs). These multidomain glycoproteins contain a number of cysteine-rich sequence repeats which resemble precursor epidermal growth factor domains (EGF-like domains) interspersed with eight-cysteine motifs and so-called "hybrid" domains, which exhibit some features of both these repeats. The signature of the eight-cysteine mot

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Sarver, Michael. "STRUCTURE-BASED MULTIPLE RNA SEQUENCE ALIGNMENT AND FINDING RNA MOTIFS." Bowling Green State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1151076710.

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Roll, James Elwood. "Inferring RNA 3D Motifs from Sequence." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1557482505513958.

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Hébert, David. "Structure de poids : homologique & motivique." Paris 13, 2012. http://www.theses.fr/2012PA132006.

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L’objet de cette thèse est l’étude des structures de poids et leurs applications au monde motivique, en particulier aux motifs de Beilinson, version relative des motifs de Voevodsky, introduits et étudiés par Ayoub, Cisinski et Déglise. Le résultat principal construit une structure de poids sur cette catégorie coïncidant, lorsque la base est un corps, avec la structure précédemment établie par Bondarko sur la catégorie des motifs de Voevodsky. Il est accompagné d’un théorème de fonctorialité et de divers applications : poids des motifs, complexe de poids à la Gillet-Soulé, caractéristique d’Eu

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Carpentier, Mathilde. "Méthodes de détection des similarités structurales : caractérisation des motifs conservés dans les familles de structures pour l' annotation des génomes." Paris 6, 2005. http://www.theses.fr/2005PA066571.

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Filling, Charlotta. "Short-chain dehydrogenases/reductases : structure, function and motifs of hydroxysteroid dehydrogenases /." Stockholm, 2002. http://diss.kib.ki.se/2002/91-7349-371-6/.

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Crowley, Louis J. "Structure-function studies of conserved sequence motifs of cytochrome b5 reductase." [Tampa, Fla] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0001913.

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Books on the topic "Structure de motifs"

1

Berg, Sandra Beth. The book of Esther: Motifs, themes and structure. UMI, 1986.

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Frye, Northrop. [The secular scripture: A study of the structure of romance. Hosei University Press, 1999.

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Littlewood, Trevor D. Helix-loop-helix transcription factors. 3rd ed. Oxford University Press, 1998.

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Steeg, Evan W. Automated motif discovery in protein structure prediction. University of Toronto, Dept. of Computer Science, 1997.

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Secrets of screenplay structure: How to recognize and emulate the structural frameworks of great films. Lone Eagle Pub., 1999.

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Between sheol and temple: Motif structure and function in the I-Psalms. Sheffield Academic Press, 1995.

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Yukarıçukurova masallarında motif ve tip araştırması. T.C. Kültür Bakanlığı, 2001.

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C, Vassilicos J., and Hunt Julian C. R, eds. Turbulence structure and vortex dynamics. Cambridge University Press, 2000.

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Kallas, Christina. Creative screenwriting: Understanding emotional structure. Palgrave Macmillan, 2010.

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Vassilicos, J. C., and Julian C. R. Hunt. Turbulence structure and vortex dynamics. Cambridge University Press, 2011.

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Book chapters on the topic "Structure de motifs"

1

Nilmeier, Jerome P., Elaine C. Meng, Benjamin J. Polacco, and Patricia C. Babbitt. "3D Motifs." In From Protein Structure to Function with Bioinformatics. Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1069-3_11.

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Rammensee, Hans-Georg, Jutta Bachmann, and Stefan Stevanović. "The Structure." In MHC Ligands and Peptide Motifs. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-662-22162-4_3.

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Novak, Walter R. P. "Tertiary Structure Domains, Folds, and Motifs." In Molecular Life Sciences. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6436-5_15-3.

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Novak, Walter R. P. "Tertiary Structure Domains, Folds and Motifs." In Molecular Life Sciences. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-1531-2_15.

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Yesselman, Joseph D., and Rhiju Das. "Modeling Small Noncanonical RNA Motifs with the Rosetta FARFAR Server." In RNA Structure Determination. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6433-8_12.

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Krzyzosiak, W. J., M. Napierala, and M. Drozdz. "RNA Structure Modules with Trinucleotide Repeat Motifs." In RNA Biochemistry and Biotechnology. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4485-8_22.

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Unger, Ron. "Short Structural Motifs: Definition, Identification, and Applications." In The Protein Folding Problem and Tertiary Structure Prediction. Birkhäuser Boston, 1994. http://dx.doi.org/10.1007/978-1-4684-6831-1_11.

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Tsigelny, Igor, Takehiko Matsumura, Thomas Südhof, and Palmer Taylor. "Metal Binding Motifs in Cholinesterases and Neuroligins." In Structure and Function of Cholinesterases and Related Proteins. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4899-1540-5_112.

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Bernstein, J., and R. E. Davis. "Graph Set Analysis of Hydrogen Bond Motifs." In Implications of Molecular and Materials Structure for New Technologies. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4653-1_20.

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Pathak, Sudipta, Vamsi Krishna Kundeti, Martin R. Schiller, and Sanguthevar Rajasekaran. "A Structure Based Algorithm for Improving Motifs Prediction." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39159-0_22.

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Conference papers on the topic "Structure de motifs"

1

Wang, Xueyi, Jun Huan, Jack S. Snoeyink, and Wei Wang. "Mining RNA Tertiary Motifs with Structure Graphs." In 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007). IEEE, 2007. http://dx.doi.org/10.1109/ssdbm.2007.38.

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"Asymmetry of motifs conservation within composite elements." In Bioinformatics of Genome Regulation and Structure/ Systems Biology. institute of cytology and genetics siberian branch of the russian academy of science, Novosibirsk State University, 2020. http://dx.doi.org/10.18699/bgrs/sb-2020-032.

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Anwar, Mohammad, and Marcel Turcotte. "Evaluation of RNA Secondary Structure Motifs using Regression Analysis." In 2006 Canadian Conference on Electrical and Computer Engineering. IEEE, 2006. http://dx.doi.org/10.1109/ccece.2006.277314.

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Sudarwati, Sudarwati, Anik Cahyaning Rahayu, and Novi Andari. "Motifs of Narrative Structure of Sacred Tombs in Surabaya." In International Conference of Communication Science Research (ICCSR 2018). Atlantis Press, 2018. http://dx.doi.org/10.2991/iccsr-18.2018.102.

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AUNG, ZEYAR, and JINYAN LI. "MINING SUPER-SECONDARY STRUCTURE MOTIFS FROM 3D PROTEIN STRUCTURES: A SEQUENCE ORDER INDEPENDENT APPROACH." In Proceedings of the 18th International Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2007. http://dx.doi.org/10.1142/9781860949852_0002.

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TANG, THOMAS, JINBO XU, and MING LI. "DISCOVERING SEQUENCE-STRUCTURE MOTIFS FROM PROTEIN SEGMENTS AND TWO APPLICATIONS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702456_0035.

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Medina, Andres, Andrew Takayama, Ankita Mohapatra, and Stevan Pecic. "Predicting motifs and secondary structure of steroid aptamers using APTANI." In 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2023. http://dx.doi.org/10.1109/ccwc57344.2023.10099310.

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"Interpreting non-coding genome variation with DNA sequence motifs." In 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/bgrs/sb-2022-038.

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"Interpreting non-coding genome variation with DNA sequence motifs." In 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-2022-038.

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Liu, Zhi-Ping. "Systematic identification of local structure binding motifs in protein-RNA recognition." In 2014 8th International Conference on Systems Biology (ISB). IEEE, 2014. http://dx.doi.org/10.1109/isb.2014.6990735.

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Reports on the topic "Structure de motifs"

1

Opella, S. J. Structural biology of the sequestration and transport of heavy metal toxins: NMR structure determination of proteins containing the -Cys-X-Y-Cys-metal binding motifs. 1997 annual progress report. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/13583.

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Opella, S. J. Structural biology of the sequestration and transport of heavy metal toxins: NMR structure determination of roteins containing the -Cys-X-Y-Cys-metal binding motifs. 1998 annual progress report. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/13584.

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Vultur, Mircea, Lucie Enel, Louis-Pierre Barette, and Simon Viviers. Les travailleurs des plateformes numériques de transport de personnes et de livraison de repas au Québec : profil et motivations. CIRANO, 2022. http://dx.doi.org/10.54932/xpzk8254.

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Cette étude vise deux objectifs : a) établir un profil des travailleurs qui utilisent une plateforme numérique de transport de personne et/ou de livraison de repas au Québec et b) d’analyser les motifs sous-jacents à leur engagement dans le travail sur une plateforme numérique. La structure des analyses se décline comme suit : dans une première partie, sur la base d’une revue de la littérature, nous présentons les caractéristiques des travailleurs des plateformes et divers types de motivations pour s’engager dans l’emploi sur les plateformes. Nous y exposons également le protocole méthodologiq

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Thompson, William B. Structure from Motion. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada175059.

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Ritchie, Elizabeth A. Tropical Cyclone Structure and Motion. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada610205.

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Ritchie, Elizabeth A., R. L. Elsberry, and P. A. Harr. Tropical Cyclone Structure and Motion. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada630661.

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Ritchie, Elizabeth A. Tropical Cyclone Structure and Motion. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada625681.

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Mazzoni, Silvia, Nicholas Gregor, Linda Al Atik, Yousef Bozorgnia, David Welch, and Gregory Deierlein. Probabilistic Seismic Hazard Analysis and Selecting and Scaling of Ground-Motion Records (PEER-CEA Project). Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, 2020. http://dx.doi.org/10.55461/zjdn7385.

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This report is one of a series of reports documenting the methods and findings of a multi-year, multi-disciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER) and funded by the California Earthquake Authority (CEA). The overall project is titled “Quantifying the Performance of Retrofit of Cripple Walls and Sill Anchorage in Single-Family Wood-Frame Buildings,” henceforth referred to as the “PEER–CEA Project.” The overall objective of the PEER–CEA Project is to provide scientifically based information (e.g., testing, analysis, and resulting loss models) that

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Todd, James T. Visual Perception of Structure from Motion. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada253235.

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Harr, Patrick A. Tropical Cyclone Formation/Structure/Motion Studies. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada548344.

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