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Artykuły w czasopismach na temat "Protein association"

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Grueninger, D., N. Treiber, M. O. P. Ziegler, J. W. A. Koetter, M. S. Schulze, and G. E. Schulz. "Designed Protein-Protein Association." Science 319, no. 5860 (2008): 206–9. http://dx.doi.org/10.1126/science.1150421.

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Pan, Albert C., Daniel Jacobson, Konstantin Yatsenko, Duluxan Sritharan, Thomas M. Weinreich, and David E. Shaw. "Atomic-level characterization of protein–protein association." Proceedings of the National Academy of Sciences 116, no. 10 (2019): 4244–49. http://dx.doi.org/10.1073/pnas.1815431116.

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Despite the biological importance of protein–protein complexes, determining their structures and association mechanisms remains an outstanding challenge. Here, we report the results of atomic-level simulations in which we observed five protein–protein pairs repeatedly associate to, and dissociate from, their experimentally determined native complexes using a molecular dynamics (MD)–based sampling approach that does not make use of any prior structural information about the complexes. To study association mechanisms, we performed additional, conventional MD simulations, in which we observed num
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Suratanee, Apichat, and Kitiporn Plaimas. "Heterogeneous Network Model to Identify Potential Associations Between Plasmodium vivax and Human Proteins." International Journal of Molecular Sciences 21, no. 4 (2020): 1310. http://dx.doi.org/10.3390/ijms21041310.

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Integration of multiple sources and data levels provides a great insight into the complex associations between human and malaria systems. In this study, a meta-analysis framework was developed based on a heterogeneous network model for integrating human-malaria protein similarities, a human protein interaction network, and a Plasmodium vivax protein interaction network. An iterative network propagation was performed on the heterogeneous network until we obtained stabilized weights. The association scores were calculated for qualifying a novel potential human-malaria protein association. This m
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Camacho, Carlos J., and Sandor Vajda. "Protein–protein association kinetics and protein docking." Current Opinion in Structural Biology 12, no. 1 (2002): 36–40. http://dx.doi.org/10.1016/s0959-440x(02)00286-5.

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Giles, K. "Interactions underlying subunit association in cholinesterases." Protein Engineering Design and Selection 10, no. 6 (1997): 677–85. http://dx.doi.org/10.1093/protein/10.6.677.

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Erickson, Harold P. "Co-operativity in protein-protein association." Journal of Molecular Biology 206, no. 3 (1989): 465–74. http://dx.doi.org/10.1016/0022-2836(89)90494-4.

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Lumry, R., and R. B. Gregory. "Dynamical factors in protein-protein association." Journal of Molecular Liquids 42 (October 1989): 113–44. http://dx.doi.org/10.1016/0167-7322(89)80029-7.

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Karplus, M., and J. Janin. "Comment on: `The entropy cost of protein association'." Protein Engineering, Design and Selection 12, no. 3 (1999): 185–86. http://dx.doi.org/10.1093/protein/12.3.185.

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Brandsdal, B. O., and A. O. Smalås. "Evaluation of protein–protein association energies by free energy perturbation calculations." Protein Engineering, Design and Selection 13, no. 4 (2000): 239–45. http://dx.doi.org/10.1093/protein/13.4.239.

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Zhou, Chun, Qimeng Wu, Ziliang Ye, et al. "Inverse Association Between Variety of Proteins With Appropriate Quantity From Different Food Sources and New-Onset Hypertension." Hypertension 79, no. 5 (2022): 1017–27. http://dx.doi.org/10.1161/hypertensionaha.121.18222.

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The relationships of the variety and quantity of different sources of dietary proteins with hypertension remain uncertain. We aimed to investigate associations between the variety and quantity of proteins intake from 8 major food sources and new-onset hypertension among 12 177 participants from the China Health and Nutrition Survey. Dietary intake was measured by 3 consecutive 24-hour dietary recalls combined with a household food inventory. The variety score of protein sources was defined as the number of protein sources consumed at the appropriate level, accounting for types and quantity of
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Rozprawy doktorskie na temat "Protein association"

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Romero, Durana Miguel Alfonso. "Improving the description of protein-protein association energy." Doctoral thesis, Universitat de Barcelona, 2018. http://hdl.handle.net/10803/665466.

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Proteins play a crucial role in virtually every biological process taking place within our cells. Most of the times, proteins do not participate in these processes alone but forming complexes of two or more proteins. Therefore, the study of protein-protein interactions (PPIs) and complex formation has become an important field of research in the last decades due to its scientific relevance and therapeutic interest. Protein docking is one of the several computational approaches that have been applied to study protein interactions over the last years. It aims to determine the three-dimensional s
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Samuel, Jarvie John. "Elicitation of Protein-Protein Interactions from Biomedical Literature Using Association Rule Discovery." Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc30508/.

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Extracting information from a stack of data is a tedious task and the scenario is no different in proteomics. Volumes of research papers are published about study of various proteins in several species, their interactions with other proteins and identification of protein(s) as possible biomarker in causing diseases. It is a challenging task for biologists to keep track of these developments manually by reading through the literatures. Several tools have been developed by computer linguists to assist identification, extraction and hypotheses generation of proteins and protein-protein interactio
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Ahmad, Mazen [Verfasser], and Volkhard [Akademischer Betreuer] Helms. "Mechanisms of protein-protein association : atomistic molecular dynamics study of the association process / Mazen Ahmad. Betreuer: Volkhard Helms." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2012. http://d-nb.info/1052551688/34.

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Donnini, S. (Serena). "Computing free energies of protein-ligand association." Doctoral thesis, University of Oulu, 2007. http://urn.fi/urn:isbn:9789514285745.

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Abstract Spontaneous changes in protein systems, such as the binding of a ligand to an enzyme or receptor, are characterized by a decrease of free energy. Despite the recent developments in computing power and methodology, it remains challenging to accurately estimate free energy changes. Major issues are still concerned with the accuracy of the underlying model to describe the protein system and how well the calculation in fact emulates the behaviour of the system. This thesis is largely concerned with the quality of current free energy calculation methods as applied to protein-ligand system
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Doig, Andrew James. "Thermodynamics of peptide association and protein folding." Thesis, University of Cambridge, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386389.

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Irudayam, Sheeba Jem. "Thermodynamics of Protein-Ligand Association and Hydration." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506575.

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Morrow, Robert Peter. "A study into human erythrocyte membrane protein association." Thesis, University of Bristol, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288406.

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Li, X. F. "Investigation of protein-protein interactions : multibody docking, association/dissociation kinetics and macromolecular crowding." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1302277/.

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Protein-protein interactions are central to understanding how cells carry out their wide array of functions and metabolic procedures. Conventional studies on specific protein interactions focus either on details of one-to-one binding interfaces, or on large networks that require a priori knowledge of binding strengths. Moreover, specific protein interactions, occurring within a crowded macromolecular environment, which is precisely the case for interactions in a real cell, are often under-investigated. A macromolecular simulation package, called BioSimz, has been developed to perform Langevin
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Huang, Wenhui. "Towards constructing disease relationship networks using genome-wide association studies." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/46326.

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Background: Genome-wide association studies (GWAS) prove to be a powerful approach to identify the genetic basis of various human[1] diseases. Here we take advantage of existing GWAS data and attempt to build a framework to understand the complex relationships among diseases. Specifically, we examined 49 diseases from all available GWAS with a cascade approach by exploiting network analysis to study the single nucleotide polymorphisms (SNP) effect on the similarity between different diseases. Proteins within perturbation subnetwork are considered to be connection points between the disease sim
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Jaeger, Samira. "Network-based inference of protein function and disease-gene association." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16623.

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Proteininteraktionen sind entscheidend für zelluläre Funktion. Interaktionen reflektieren direkte funktionale Beziehungen zwischen Proteinen. Veränderungen in spezifischen Interaktionsmustern tragen zur Entstehung von Krankheiten bei. In dieser Arbeit werden funktionale und pathologische Aspekte von Proteininteraktionen analysiert, um Funktionen für bisher nicht charakterisierte Proteine vorherzusagen und Proteine mit Krankheitsphänotypen zu assoziieren. Verschiedene Methoden wurden in den letzten Jahren entwickelt, die die funktionalen Eigenschaften von Proteinen untersuchen. Dennoch bleibt
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Książki na temat "Protein association"

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Przytycka, Teresa, and Anna Panchenko. Protein-protein interactions and networks: Identification, computer analysis, and prediction. Springer, 2010.

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Anna, Panchenko, and Przytycka Teresa, eds. Protein-protein interactions and networks: Identification, computer analysis, and prediction. Springer, 2008.

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Anna, Panchenko, and Przytycka Teresa, eds. Protein-protein interactions and networks: Identification, computer analysis, and prediction. Springer, 2008.

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International Workshop on the CCN Family of Genes (5th 2008 Toronto, Canada). CCN proteins in health and disease: An overview of the Fifth International Workshop on the CCN Family of Genes. Edited by Perbal Annick, Takigawa Masaharu, and Perbal Bernard V. Springer, 2010.

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Ren-Jang, Lin, ed. RNA-protein interaction protocols. 2nd ed. Humana, 2008.

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1980-, Guzzi Pietro Hiram, ed. Data management of protein interaction networks. Wiley, 2012.

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Olds, James. A role for protein kinase C in associative learning. National Institute of Neurological and Communicative Disorders and Stroke, 1993.

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M, Bujnicki Janusz, ed. Prediction of protein structures, functions, and interactions. John Wiley & Sons, 2008.

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Johnson, Michael L., Jo M. Holt, and Gary K. Ackers. Biothermodynamics. Elsevier/Academic Press, 2011.

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1969-, Li Xiao-Li, and Ng See-Kiong, eds. Biological data mining in protein interaction networks. Medical Information Science Reference, 2009.

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Części książek na temat "Protein association"

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Ross, Philip D. "Thermodynamics of Protein-Protein Association." In Thermodynamic Data for Biochemistry and Biotechnology. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71114-5_8.

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Yon-Kahn, Jeannine, and Guy Hervé. "Protein-Ligand Association Equilibria." In Molecular and Cellular Enzymology. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01228-0_3.

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Baron, Riccardo, Piotr Setny, and J. Andrew McCammon. "Hydrophobic Association and Volume-Confined Water Molecules." In Protein-Ligand Interactions. Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527645947.ch8.

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Powers, Evan T., and Frank A. Ferrone. "Kinetic Models for Protein Misfolding and Association." In Protein Misfolding Diseases. John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470572702.ch4.

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Ben-Naim, Arieh. "Solvent Effects on Protein Stability and Protein Association." In Protein-Solvent Interactions. CRC Press, 2024. http://dx.doi.org/10.1201/9781003573937-9.

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Jaenicke, R. "Protein Stability, Folding and Association." In Immobilised Macromolecules: Application Potentials. Springer London, 1993. http://dx.doi.org/10.1007/978-1-4471-3479-4_1.

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Chen, Qingfeng. "Protein Structure Prediction." In Association Analysis Techniques and Applications in Bioinformatics. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8251-6_7.

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Brems, David N., Patricia L. Brown, Christopher Bryant, et al. "Altering the Self-Association and Stability of Insulin by Amino Acid Replacement." In Protein Folding. American Chemical Society, 1993. http://dx.doi.org/10.1021/bk-1993-0526.ch019.

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Hamilton, W., J. E. Borgert, T. Hamelryck, and J. S. Marron. "Persistent Topology of Protein Space." In Association for Women in Mathematics Series. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95519-9_10.

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Ufer, Guido, Peter Dörmann, and Dorothea Bartels. "Studying Lipid–Protein Interactions Using Protein–Lipid Overlay and Protein–Liposome Association Assays." In Methods in Molecular Biology. Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1362-7_22.

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Streszczenia konferencji na temat "Protein association"

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Li, Ziwen, Xiang Chen, and Youngseung Jeon. "GraPPI: A Retrieve-Divide-Solve GraphRAG Framework for Large-scale Protein-protein Interaction Exploration." In Findings of the Association for Computational Linguistics: NAACL 2025. Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.findings-naacl.201.

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Liu, Zhiyuan, An Zhang, Hao Fei, et al. "ProtT3: Protein-to-Text Generation for Text-based Protein Understanding." In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.acl-long.324.

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Zhuo, Le, Zewen Chi, Minghao Xu, et al. "ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training." In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.acl-long.484.

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Wang, Zeyuan, Qiang Zhang, Keyan Ding, et al. "InstructProtein: Aligning Human and Protein Language via Knowledge Instruction." In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.acl-long.62.

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Bose, Urmi, Mehedi Hasan Roman, Md Rakibul Hasan, Denesh Das, and Bikash Kumar Paul. "Exploring Protein-Protein Interactions Network, Prediction of Drugs and Association of Genes with Diseases Among Anxiety, Insomnia and Depression: A Computational Biology Approach." In 2024 2nd International Conference on Information and Communication Technology (ICICT). IEEE, 2024. https://doi.org/10.1109/icict64387.2024.10839659.

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Kim, Yunsoo. "Foundation Model for Biomedical Graphs: Integrating Knowledge Graphs and Protein Structures to Large Language Models." In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.acl-srw.30.

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Jararweh, Ala, Oladimeji Macaulay, David Arredondo, et al. "Protein2Text: Resampling Mechanism to Translate Protein Sequences into Human-Interpretable Text." In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.naacl-industry.68.

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Garcia, Beatriz, Ricardo Aler, Agapito Ledezma, and Araceli Sanchis. "Protein-protein functional association prediction using genetic programming." In the 10th annual conference. ACM Press, 2008. http://dx.doi.org/10.1145/1389095.1389156.

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Hung, Fei-Hung, and Hung-Wen Chiu. "Protein-Protein Interaction Prediction based on Association Rules of Protein Functional Regions." In 2007 Second International Conference on Innovative Computing, Information and Control. IEEE, 2007. http://dx.doi.org/10.1109/icicic.2007.466.

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Solernou, Albert, Juan Fernandez-Recio, Jesús Clemente-Gallardo, et al. "Computational Tools for Exploration of the Energy Landscape in Protein-Protein Association." In LARGE SCALE SIMULATIONS OF COMPLEX SYSTEMS, CONDENSED MATTER AND FUSION PLASMA: Proceedings of the BIFI2008 International Conference: Large Scale Simulations of Complex Systems, Condensed Matter and Fusion Plasma. AIP, 2008. http://dx.doi.org/10.1063/1.3033364.

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Raporty organizacyjne na temat "Protein association"

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Loebenstein, Gad, William Dawson, and Abed Gera. Association of the IVR Gene with Virus Localization and Resistance. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7604922.bard.

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We have reported that localization of TMV in tobacco cultivars with the N gene, is associated with a 23 K protein (IVR) that inhibited replication of several plant viruses. This protein was also found in induced resistant tissue of Nicotiana glutinosa x Nicotiana debneyi. During the present grant we found that TMV production is enhanced in protoplasts and plants of local lesion responding tobacco cultivars exposed to 35oC, parallel to an almost complete suppression of the production of IVR. We also found that IVR is associated with resistance mechanisms in pepper cultivars. We succeeded to clo
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Epel, Bernard L., Roger N. Beachy, A. Katz, et al. Isolation and Characterization of Plasmodesmata Components by Association with Tobacco Mosaic Virus Movement Proteins Fused with the Green Fluorescent Protein from Aequorea victoria. United States Department of Agriculture, 1999. http://dx.doi.org/10.32747/1999.7573996.bard.

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The coordination and regulation of growth and development in multicellular organisms is dependent, in part, on the controlled short and long-distance transport of signaling molecule: In plants, symplastic communication is provided by trans-wall co-axial membranous tunnels termed plasmodesmata (Pd). Plant viruses spread cell-to-cell by altering Pd. This movement scenario necessitates a targeting mechanism that delivers the virus to a Pd and a transport mechanism to move the virion or viral nucleic acid through the Pd channel. The identity of host proteins with which MP interacts, the mechanism
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Adhami, Vaqar M. Association Between Microtubule Associated Protein -2 and the EGRF Signaling in Breast Cancer. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada445117.

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Adhami, Vaqar M. Association between Microtubule Associated Protein -2 and the EGRF Signaling in Breast Cancer. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada466580.

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Zhou, Kechong, Yi Lu, Kang Liu, Yuxuan Song, Yongjiao Yang, and Xiaoqiang Liu. Association between C-reactive protein levels and prognosis in prostate cancer: A meta-analysis involving 13,555 subjects. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.6.0061.

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Gontar, I. P., O. A. Rusanova, O. I. Emelyanova, and I. A. Zborovskaya. ASSOCIATION BETWEEN NEUROLOGICAL STATUS OF RHEUMATOID ARTHRITIS PATIENTS WITH SPECIFIC ANTIBODIES TO MYELIN AND S-100 PROTEIN. Планета, 2018. http://dx.doi.org/10.18411/978-5-907109-24-7-2018-xxxv-89-95.

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Lamina, Toyin, Sallee Brandt, Hamdi I. Abdi, et al. The Effect of Protein Intake on Health: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), 2024. http://dx.doi.org/10.23970/ahrqepcsrproteinhealth.

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Objective. This review examines the association between dietary protein intake and the risk of bone disease, kidney disease, and sarcopenia, aiming to inform future Dietary Reference Intakes (DRIs) updates, including the development of a Chronic Disease Risk Reduction (CDRR) reference value for protein. Data sources. We searched MEDLINE®, Embase®, AGRICOLA, and Scopus from January 2000 to May 2024, and supplemented by citation searching of relevant reviews and original research. Review methods. Following the Agency for Healthcare Research and Quality Methods Guide for Effectiveness and Compara
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Suriyaphol, Gunnaporn. Study the gene expression of E-cadherin, syndecan1, matrix metalloproteinases-2, -7, -9, -14 and tissue inhibitors of metalloproteinases-1 and -2 in canine oral melanoma. Chulalongkorn University, 2015. https://doi.org/10.58837/chula.res.2015.80.

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The objectives of this study were to 1.) select the suitable reference genes for quantitative real-time polymerse chain reaction in the most common canine oral cancers: oral melanoma (OM) and oral squamous cell carcinoma (OSCC), 2.) study the gene expression of E-cadherin (CDH1), syndecan 1 (SDC1), matrix metalloproteinases-2, -7, -9, -14 (MMP2, MMP7, MMP9, MMP14) and tissue inhibitors of metalloproteinases-1 and -2 (TIMP1, TIMP2) in canine OM at the mRNA level and study the CDH1, SDC1 and Ki-67 protein expression by immunohistochemistry, and 3.) study the association of gene expression and th
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Blaxter, Tamsin, and Tara Garnett. Primed for power: a short cultural history of protein. TABLE, 2022. http://dx.doi.org/10.56661/ba271ef5.

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Protein has a singularly prominent place in discussions about food. It symbolises fitness, strength and masculinity, motherhood and care. It is the preferred macronutrient of affluence and education, the mark of a conscientious diet in wealthy countries and of wealth and success elsewhere. Through its association with livestock it stands for pastoral beauty and tradition. It is the high-tech food of science fiction, and in discussions of changing agricultural systems it is the pivotal nutrient around which good and bad futures revolve. There is no denying that we need protein and that engaging
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Ohad, Nir, and Robert Fischer. Regulation of Fertilization-Independent Endosperm Development by Polycomb Proteins. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7695869.bard.

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Arabidopsis mutants that we have isolated, encode for fertilization-independent endosperm (fie), fertilization-independent seed2 (fis2) and medea (mea) genes, act in the female gametophyte and allow endosperm to develop without fertilization when mutated. We cloned the FIE and MEA genes and showed that they encode WD and SET domain polycomb (Pc G) proteins, respectively. Homologous proteins of FIE and MEA in other organisms are known to regulate gene transcription by modulating chromatin structure. Based on our results, we proposed a model whereby both FIE and MEA interact to suppress transcri
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