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Artykuły w czasopismach na temat "Interactive molecular simulations"
Rapaport, D. C., i Harvey Gould. "An introduction to interactive molecular-dynamics simulations". Computers in Physics 11, nr 4 (1997): 337. http://dx.doi.org/10.1063/1.168612.
Pełny tekst źródłaLanrezac, André, Benoist Laurent, Hubert Santuz, Nicolas Férey i Marc Baaden. "Fast and Interactive Positioning of Proteins within Membranes". Algorithms 15, nr 11 (7.11.2022): 415. http://dx.doi.org/10.3390/a15110415.
Pełny tekst źródłaDelalande, Olivier, Nicolas Férey, Gilles Grasseau i Marc Baaden. "Complex molecular assemblies at hand via interactive simulations". Journal of Computational Chemistry 30, nr 15 (30.11.2009): 2375–87. http://dx.doi.org/10.1002/jcc.21235.
Pełny tekst źródłaLahlali, Abdelouahed, Nadia Chafiq, Mohamed Radid, Kamal Moundy i Chaibia Srour. "The Effect of Integrating Interactive Simulations on the Development of Students’ Motivation, Engagement, Interaction and School Results". International Journal of Emerging Technologies in Learning (iJET) 18, nr 12 (21.06.2023): 193–207. http://dx.doi.org/10.3991/ijet.v18i12.39755.
Pełny tekst źródłaDunn, Justin, i Umesh Ramnarain. "The Effect of Simulation-Supported Inquiry on South African Natural Sciences Learners’ Understanding of Atomic and Molecular Structures". Education Sciences 10, nr 10 (14.10.2020): 280. http://dx.doi.org/10.3390/educsci10100280.
Pełny tekst źródłaGoret, G., B. Aoun i E. Pellegrini. "MDANSE: An Interactive Analysis Environment for Molecular Dynamics Simulations". Journal of Chemical Information and Modeling 57, nr 1 (6.01.2017): 1–5. http://dx.doi.org/10.1021/acs.jcim.6b00571.
Pełny tekst źródłaWhite, Brian T., i Ethan D. Bolker. "Interactive computer simulations of genetics, biochemistry, and molecular biology". Biochemistry and Molecular Biology Education 36, nr 1 (styczeń 2008): 77–84. http://dx.doi.org/10.1002/bmb.20152.
Pełny tekst źródłaSego, T. J., James P. Sluka, Herbert M. Sauro i James A. Glazier. "Tissue Forge: Interactive biological and biophysics simulation environment". PLOS Computational Biology 19, nr 10 (23.10.2023): e1010768. http://dx.doi.org/10.1371/journal.pcbi.1010768.
Pełny tekst źródłaCruz-neira, C., R. Langley i P. A. Bash. "Interactive Molecular Modeling with Virtual Reality and Empirical Energy Simulations". SAR and QSAR in Environmental Research 9, nr 1-2 (styczeń 1998): 39–51. http://dx.doi.org/10.1080/10629369808039148.
Pełny tekst źródłaMcCluskey, Andrew R., James Grant, Adam R. Symington, Tim Snow, James Doutch, Benjamin J. Morgan, Stephen C. Parker i Karen J. Edler. "An introduction to classical molecular dynamics simulation for experimental scattering users". Journal of Applied Crystallography 52, nr 3 (7.05.2019): 665–68. http://dx.doi.org/10.1107/s1600576719004333.
Pełny tekst źródłaRozprawy doktorskie na temat "Interactive molecular simulations"
Ashe, Colin Alexander. "Interactive online simulations and curriculum for teaching and learning fundamental concepts in molecular science at the undergraduate level". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/59212.
Pełny tekst źródłaIncludes bibliographical references (p. 213-218).
The number of research disciplines that focus, at least in part, on the atomic or molecular level is rapidly increasing. As a result, the concepts that describe the behavior of atoms and molecules, known collectively as "Molecular Science", are becoming an educational necessity for an expanding fraction of college and university students. Unfortunately, these concepts are challenging for students to learn. Because of the growing importance of these concepts and their difficulty, a project was undertaken with the goal of helping students to understand these concepts using simplified, interactive models. Students in their first year of undergraduate study were targeted. The primary goal of the project was to help students understand the so-called "energy landscape", also known as the "potential energy surface". This concept is central to Molecular Science because it contains information about both equilibrium and kinetic properties of a system. It is also widely used in textbooks and by experts for reasoning qualitatively. Interactive simulations, along with related curriculum, were created in order to help students understand the energy landscape and explore its implications. The simulations visualize simplified models, which were chosen for their analogic connection to chemical systems as well as their similarity to things with which students could intuitively relate. The primary models used were two- and three-dimensional cardboard boxes, as well as a series of platforms covered with balls. The models were simulated and visualized in Java applets. Curriculum sequences consisting of applets, exercises, and explanations were carefully constructed to present concepts in a logical order. The materials were made available online at MatDL.org, the materials pathway of the National Science Digital Library. The curriculum sequences were used as a supplemental exercise by students at Kent State University, Carnegie Mellon University (CMU), and the Massachusetts Institute of Technology (MIT). Two large assessments of student learning were conducted: one at CMU and one at MIT, involving over 400 total students. Assessment results demonstrated that using the project materials improved students' performance on the assessment tests with a greater than 99.9% degree of confidence. Free response comments indicated that students found the exercises helpful and interesting.
by Colin Alexander Ashe.
Ph.D.
Lanrezac, André. "Interprétation de données expérimentales par simulation et visualisation moléculaire interactive". Electronic Thesis or Diss., Université Paris Cité, 2023. http://www.theses.fr/2023UNIP7133.
Pełny tekst źródłaThe goal of Interactive Molecular Simulations (IMS) is to observe the conformational dynamics of a molecular simulation in real-time. Instant visual feedback enables informative monitoring and observation of structural changes imposed by the user's manipulation of the IMS. I conducted an in-depth study of knowledge to gather and synthesize all the research that has developed IMS. Interactive Molecular Dynamics (IMD) is one of the first IMS protocols that laid the foundation for the development of this approach. My thesis laboratory was inspired by IMD to develop the BioSpring simulation engine based on the elastic network model. This model allows for the simulation of the flexibility of large biomolecular ensembles, potentially revealing long-timescale changes that would not be easily captured by molecular dynamics. This simulation engine, along with the UnityMol visualization software, developed through the Unity3D game engine, and linked by the MDDriver communication interface, has been extended to converge towards a complete software suite. The goal is to provide an experimenter, whether an expert or novice, with a complete toolbox for modeling, displaying, and interactively controlling all parameters of a simulation. The particular implementation of such a protocol, based on formalized and extensible communication between the different components, was designed to easily integrate new possibilities for interactive manipulation and sets of experimental data that will be added to the restraints imposed on the simulation. Therefore, the user can manipulate the molecule of interest under the control of biophysical properties integrated into the simulated model, while also having the ability to dynamically adjust simulation parameters. Furthermore, one of the initial objectives of this thesis was to integrate the management of ambiguous interaction constraints from the HADDOCK biomolecular docking software directly into UnityMol, making it possible to use these same restraints with a variety of simulation engines. A primary focus of this research was to develop a fast and interactive protein positioning algorithm in implicit membranes using a model called the Integrative Membrane Protein and Lipid Association Method (IMPALA), developed by Robert Brasseur's team in 1998. The first step was to conduct an in-depth search of the conditions under which the experiments were performed at the time to verify the method and validate our own implementation. We will see that this opens up interesting questions about how scientific experiments can be reproduced. The final step that concluded this thesis was the development of a new universal lipid-protein interaction method, UNILIPID, which is an interactive protein incorporation model in implicit membranes. It is independent of the representation scale and can be applied at the all-atom, coarse-grain, or grain-by-grain level. The latest Martini3 representation, as well as a Monte Carlo sampling method and rigid body dynamics simulation, have been specially integrated into the method, in addition to various system preparation tools. Furthermore, UNILIPID is a versatile approach that precisely reproduces experimental hydrophobicity terms for each amino acid. In addition to simple implicit membranes, I will describe an analytical implementation of double membranes as well as a generalization to arbitrarily shaped membranes, both of which rely on novel applications
Cardona, Amengual Javier. "Molecular simulations of the interaction of microwaves with fluids". Thesis, University of Strathclyde, 2016. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=27631.
Pełny tekst źródłaBryson, Kevin. "Molecular simulation of DNA and its interaction with polyamines". Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297070.
Pełny tekst źródłaFrança, João. "Solid-liquid interaction in ionanofluids. Experiments and molecular simulation". Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC077.
Pełny tekst źródłaOne of the main areas of research in chemistry and chemical engineering involves the use of ionic liquids and nanomaterials as alternatives to many chemical products and chemical processes, as the latter are currently considered to be environmentally non-friendly. Their possible use as new heat transfer fluids and heat storage materials, which can obey to most principles of green chemistry or green processing, requires the experimental and theoretical study of the heat transfer mechanisms in complex fluids, like the ionanofluids. It was the purpose of this dissertation to study ionanofluids, which consist on the dispersion of nanomaterials in an ionic liquid.The first objective of this work was to measure thermophysical properties of ionic liquids and ionanofluids, namely thermal conductivity, viscosity, density and heat capacity in a temperature range between -10 e 150 ºC and at atmospherical pressure. In this sense, the thermophysical properties of a considerable set of ionic liquids and ionanofluids were measured, with particular emphasis on the thermal conductivity of the fluids. The ionic liquids studied were [C2mim][EtSO4], [C4mim][(CF3SO2)2N], [C2mim][N(CN)2], [C4mim][N(CN)2], [C4mpyr][N(CN)2], [C2mim][SCN], [C4mim][SCN], [C2mim][C(CN)3], [C4mim][C(CN)3], [P66614][N(CN)2], [P66614][Br] and their suspensions with 0.5% and 1% w/w of multi-walled carbon nanotubes (MWCNTs). The results obtained show that there is a substantial enhancement of the thermal conductivity of the base fluid due to the suspension of the nanomaterial, considering both mass fractions. However, the enhancement varies significantly when considering different base ionic liquids, with a range between 2 to 30%, with increasing temperature. This fact makes it more difficult to unify the obtained information in order to obtain a model that allows predicting the enhancement of the thermal conductivity. Current models used to calculate the thermal conductivity of nanofluids present values that are considerably underestimated when compared to the experimental ones, somewhat due to the considerations on the role of the solid-liquid interface on heat transport.Considering density, the impact from the addition of MWCNTs on the base fluid’s density is very low, ranging between 0.25% and 0.5% for 0.5% w/w and 1% w/w MWCNTs, respectively. This was fairly expected and is due to the considerable difference in density between both types of materials. However, viscosity was the property for which the highest values of enhancement were verified, ranging between 28 and 245% in both mass fractions of MWCNTs. The heat capacity was the only of the four properties mentioned above not to be studied in this work due to technical issues with the calorimeter to be used. Nevertheless, the amount of data collected on the remainder thermophysical properties was extensive. It is believed that the latter contributes meaningfully to a growing database of ionic liquids and ionanofluids’ properties, while providing insight on the variation of said properties obtained from the suspension of MWCNTs in ionic liquids.The second objective of this work consisted on the development of molecular interaction models between ionic liquids and highly conductive nanomaterials, such as carbon nanotubes and graphene sheets. These models were constructed based on quantum calculations of the interaction energy between the ions and a cluster, providing interaction potentials. Once these models were obtained, a second stage on this computational approach entailed to simulate, by Molecular Dynamics methods, the interface nanomaterial/ionic liquid, in order to understand the specific interparticle/molecular interactions and their contribution to the heat transfer. This would allow to study both structural properties, such as the ordering of the ionic fluid at the interface, and dynamic ones, such as residence times and diffusion. (...)
Gacek, Sobieslaw Stanislaw. "Molecular dynamics simulation of shock waves in laser-material interaction". [Ames, Iowa : Iowa State University], 2009.
Znajdź pełny tekst źródłaHedman, Fredrik. "Algorithms for Molecular Dynamics Simulations". Doctoral thesis, Stockholm University, Department of Physical, Inorganic and Structural Chemistry, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-1008.
Pełny tekst źródłaMethods for performing large-scale parallel Molecular Dynamics(MD) simulations are investigated. A perspective on the field of parallel MD simulations is given. Hardware and software aspects are characterized and the interplay between the two is briefly discussed.
A method for performing ab initio MD is described; the method essentially recomputes the interaction potential at each time-step. It has been tested on a system of liquid water by comparing results with other simulation methods and experimental results. Different strategies for parallelization are explored.
Furthermore, data-parallel methods for short-range and long-range interactions on massively parallel platforms are described and compared.
Next, a method for treating electrostatic interactions in MD simulations is developed. It combines the traditional Ewald summation technique with the nonuniform Fast Fourier transform---ENUF for short. The method scales as N log N, where N is the number of charges in the system. ENUF has a behavior very similar to Ewald summation and can be easily and efficiently implemented in existing simulation programs.
Finally, an outlook is given and some directions for further developments are suggested.
Marchi, Davide. "Multiscale modelling of organic molecules interacting with solids". Doctoral thesis, Università del Piemonte Orientale, 2022. http://hdl.handle.net/11579/144038.
Pełny tekst źródłaHermansson, Anders. "Calculating Ligand-Protein Binding Energies from Molecular Dynamics Simulations". Thesis, KTH, Skolan för kemivetenskap (CHE), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-170722.
Pełny tekst źródłaGehrcke, Jan-Philip. "Investigation of the interleukin-10-GAG interaction using molecular simulation methods". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-163205.
Pełny tekst źródłaKsiążki na temat "Interactive molecular simulations"
Gabriele, Cruciani, red. Molecular interaction fields: Applications in drug discovery and ADME prediction. Weinheim: Wiley-VCH, 2005.
Znajdź pełny tekst źródłaRuth, Nussinov, i Schreiber Gideon, red. Computational protein-protein interactions. Boca Raton: CRC Press/Taylor & Francis, 2009.
Znajdź pełny tekst źródłaTakao, Kumazawa, Kruger Lawrence i Mizumura Kazue, red. The polymodal receptor: A gateway to pathological pain. Amsterdam: Elsevier, 1996.
Znajdź pełny tekst źródłaFolkers, Gerd, Raimund Mannhold, Hugo Kubinyi i Gabriele Cruciani. Molecular Interaction Fields: Applications in Drug Discovery and ADME Prediction. Wiley & Sons, Incorporated, John, 2006.
Znajdź pełny tekst źródłaFolkers, Gerd, Raimund Mannhold, Hugo Kubinyi i Gabriele Cruciani. Molecular Interaction Fields: Applications in Drug Discovery and ADME Prediction. Wiley-VCH Verlag GmbH, 2006.
Znajdź pełny tekst źródła(Editor), Wolfgang Alt, Mark Chaplain (Editor), Michael Griebel (Editor) i Jürgen Lenz (Editor), red. Polymer and Cell Dynamics: Multiscale Modeling and Numerical Simulations (Mathematics and Biosciences in Interaction). Birkhäuser Basel, 2003.
Znajdź pełny tekst źródłaMolecular interaction fields: Applications in drug discovery and ADME prediction. Weinheim, DE: Wiley-VCH, 2006.
Znajdź pełny tekst źródła(Editor), Gabriele Cruciani, Raimund Mannhold (Series Editor), Hugo Kubinyi (Series Editor) i Gerd Folkers (Series Editor), red. Molecular Interaction Fields: Applications in Drug Discovery and ADME Prediction (Methods and Principles in Medicinal Chemistry). Wiley-VCH, 2006.
Znajdź pełny tekst źródłaFalconi, Mattia, Arvind Ramanathan i James Leland Olds, red. Interaction of Biomolecules and Bioactive Compounds with the SARS-CoV-2 Proteins: Molecular Simulations for the fight against Covid-19. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88976-575-1.
Pełny tekst źródłaComputational Protein-Protein Interactions. CRC, 2009.
Znajdź pełny tekst źródłaCzęści książek na temat "Interactive molecular simulations"
Kamberaj, Hiqmet. "Python Interactive GUI for CHARMM Software Package". W Computer Simulations in Molecular Biology, 183–208. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34839-6_9.
Pełny tekst źródłaLejdfors, Calle, Malek O. Khan, Anders Ynnerman i Bo Jönsson. "GISMOS: Graphics and Interactive Steering of MOlecular Simulations". W Lecture Notes in Computational Science and Engineering, 154–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57313-2_17.
Pełny tekst źródłaBotello-Smith, Wesley M., i Yun Lyna Luo. "Concepts, Practices, and Interactive Tutorial for Allosteric Network Analysis of Molecular Dynamics Simulations". W Methods in Molecular Biology, 311–34. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1394-8_17.
Pełny tekst źródłaTsukanov, Alexey A., i Olga Vasiljeva. "Nanomaterials Interaction with Cell Membranes: Computer Simulation Studies". W Springer Tracts in Mechanical Engineering, 189–210. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60124-9_9.
Pełny tekst źródłaLim, Kap, i James N. Herron. "Molecular Simulation of Protein-PEG Interaction". W Poly(Ethylene Glycol) Chemistry, 29–56. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-0703-5_3.
Pełny tekst źródłaHünenberger, P. H., i W. F. van Gunsteren. "Empirical classical interaction functions for molecular simulation". W Computer Simulation of Biomolecular Systems, 3–82. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-017-1120-3_1.
Pełny tekst źródłaSchmitt, S., S. Stephan, B. Kirsch, J. C. Aurich, H. M. Urbassek i H. Hasse. "Molecular Dynamics Simulation of Cutting Processes: The Influence of Cutting Fluids at the Atomistic Scale". W Proceedings of the 3rd Conference on Physical Modeling for Virtual Manufacturing Systems and Processes, 260–80. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35779-4_14.
Pełny tekst źródłaCorongiu, G., M. Aida, M. F. Pas i E. Clementi. "Molecular Dynamics Simulations with ab initio Interaction Potentials". W Modem Techniques in Computational Chemistry: MOTECC-91, 847–919. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3032-5_21.
Pełny tekst źródłaKumar, Veerendra, i Shivani Yaduvanshi. "Protein-Protein Interaction Studies Using Molecular Dynamics Simulation". W Methods in Molecular Biology, 269–83. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3147-8_16.
Pełny tekst źródłaYamashita, Takefumi. "Molecular Dynamics Simulation for Investigating Antigen–Antibody Interaction". W Computer-Aided Antibody Design, 101–7. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2609-2_4.
Pełny tekst źródłaStreszczenia konferencji na temat "Interactive molecular simulations"
Vanderveken, D. J., G. Baudoux, D. P. Vercauteren i F. Durant. "KEMIT: Interactive Computer-Aided Molecular Design Using the PHIGS+Standard: Applications to Biomolecules". W Advances in biomolecular simulations. AIP, 1991. http://dx.doi.org/10.1063/1.41332.
Pełny tekst źródłaLietsch, Stefan, Christoph Laroque i Henning Zabel. "Computational Steering of Interactive Material Flow Simulations". W ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49405.
Pełny tekst źródłaParulek, Julius, Cagatay Turkay, Nathalie Reuter i Ivan Viola. "Implicit surfaces for interactive graph based cavity analysis of molecular simulations". W 2012 IEEE Symposium on Biological Data Visualization (BioVis). IEEE, 2012. http://dx.doi.org/10.1109/biovis.2012.6378601.
Pełny tekst źródłaJamieson-Binnie, Alexander D., Michael B. O'Connor, Jonathan Barnoud, Mark D. Wonnacott, Simon J. Bennie i David R. Glowacki. "Narupa iMD: A VR-Enabled Multiplayer Framework for Streaming Interactive Molecular Simulations". W SIGGRAPH '20: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3388536.3407891.
Pełny tekst źródłaKim, BoHung, Ali Beskok i Tahir Cagin. "Molecular Dynamics Simulations of Thermal Interactions in Nanoscale Liquid Channels". W ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67448.
Pełny tekst źródłaZhao, Ruijie, Yunfei Chen, Kedong Bi, Meihui Lin i Zan Wang. "A Modified Thermal Boundary Resistance Model for FCC Structures". W ASME 2009 Second International Conference on Micro/Nanoscale Heat and Mass Transfer. ASMEDC, 2009. http://dx.doi.org/10.1115/mnhmt2009-18175.
Pełny tekst źródłaEnemark, So̸ren, Marco A. Deriu i Monica Soncini. "Mechanical Properties of Tubulin Molecules by Molecular Dynamics Simulations". W ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95674.
Pełny tekst źródłaDarbandi, Masoud, Hossein Reza Abbasi, Moslem Sabouri i Rasool Khaledi-Alidusti. "Simulation of Heat Transfer in Nanoscale Flow Using Molecular Dynamics". W ASME 2010 8th International Conference on Nanochannels, Microchannels, and Minichannels collocated with 3rd Joint US-European Fluids Engineering Summer Meeting. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-31065.
Pełny tekst źródłaXie, Jian-Fei, i Bing-Yang Cao. "Molecular Dynamics Study on Fluid Flow in Nanochannels With Permeable Walls". W ASME 2016 5th International Conference on Micro/Nanoscale Heat and Mass Transfer. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/mnhmt2016-6421.
Pełny tekst źródłaBanerjee, Soumik. "Molecular Simulation of the Self-Agglomeration of Carbon Nanostructures in Various Chemical Environments". W ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-89697.
Pełny tekst źródłaRaporty organizacyjne na temat "Interactive molecular simulations"
Hill, Christian. International Atomic and Molecular Code Centres Network: Database Services for Radiation Damage in Nuclear Materials. IAEA Nuclear Data Section, styczeń 2020. http://dx.doi.org/10.61092/iaea.agtk-r4gy.
Pełny tekst źródłaHill, C. Summary Report of the 7th Biennial Technical Meeting of the Code Centres Network of the International Atomic and Molecular Code Centres Network: Database Services for Radiation Damage in Nuclear Materials. IAEA Nuclear Data Section, październik 2021. http://dx.doi.org/10.61092/iaea.25ex-cn8n.
Pełny tekst źródłaParra, José G., Jesús Roa i Arnaldo Armado. Exploration of the molecular interaction of a humic acid model with the water by means of molecular dynamics simulations. Peeref, marzec 2023. http://dx.doi.org/10.54985/peeref.2303p4473663.
Pełny tekst źródłaMatthews, Lisa, Guanming Wu, Robin Haw, Timothy Brunson, Nasim Sanati, Solomon Shorser, Deidre Beavers, Patrick Conley, Lincoln Stein i Peter D'Eustachio. Illuminating Dark Proteins using Reactome Pathways. Reactome, październik 2022. http://dx.doi.org/10.3180/poster/20221027matthews.
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