Relevant bibliographies by topics / Biomolecular systems

Academic literature on the topic 'Biomolecular systems'

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Published: 6 September 2023

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Journal articles on the topic "Biomolecular systems"

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Miró, Jesús M., and Alfonso Rodríguez-Patón. "Biomolecular Computing Devices in Synthetic Biology." International Journal of Nanotechnology and Molecular Computation 2, no. 2 (April 2010): 47–64. http://dx.doi.org/10.4018/978-1-59904-996-0.ch014.

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Synthetic biology and biomolecular computation are disciplines that fuse when it comes to designing and building information processing devices. In this chapter, we study several devices that are representative of this fusion. These are three gene circuits implementing logic gates, a DNA nanodevice and a biomolecular automaton. The operation of these devices is based on gene expression regulation, the so-called competitive hybridization and the workings of certain biomolecules like restriction enzymes or regulatory proteins. Synthetic biology, biomolecular computation, systems biology and standard molecular biology concepts are also defined to give a better understanding of the chapter. The aim is to acquaint readers with these biomolecular devices born of the marriage between synthetic biology and biomolecular computation.
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Katrusiak, Andrzej, Michalina Aniola, Kamil Dziubek, Kinga Ostrowska, and Ewa Patyk. "Biomolecular systems under pressure." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C1188. http://dx.doi.org/10.1107/s2053273314088111.

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Biological systems are often regarded as the ultimate goal of all knowledge in this respect that they can provide the clue for understanding the origin of life and the means for improving the life conditions and healthcare. Hence the interest in high-pressure behavior of organic and biomolecular systems. Such simple organic systems were among the first structural studies at high pressure at all. They included chloroform by Roger Fourme in 1968 [1] and benzene by Piermarini et al. in 1969, still with the use of photographic technique. The efficient studies on bio-macromolecular crystals had to wait for several decades till synchrotron radiation became more accessible and Roger Fourme again stood in the avant-garde of these studies [2]. At the turn of centuries his innovations in the laboratory equipment and experimental setup let him exploring high-pressure conformations of proteins, viral capsids and the double-helix molecular architecture in nucleic acids. These directions of high-pressure studies are continued for simple and macromolecular systems of biological importance. Recently new surprising facts were revealed about the compression of urea, sucrose, and other organic compounds, as well as of macromolecular crystals. Sugars are the main energy carriers for animals as well as building blocks in the living tissue, they are also ideal models for studying pressure-induced changes of OH···O and CH···O interactions. Different types of transformations occur in compressed urea, the first organic compound synthesized in laboratory. Hen egg-white lysozyme was investigated at moderate pressure in a beryllium vessel and the compression of both tetragonal and orthorhombic modifications were measured to 1.0 GPa in a DAC; the high-pressure structure of the tetragonal form was determined and refined at still higher pressure by Fourme et al. [3] Can high pressure provide information about the remarkable polymorphism of lysozyme?
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Niranjan, Vidya, Purushotham Rao, Akshay Uttarkar, and Jitendra Kumar. "Protocol for the development of coarse-grained structures for macromolecular simulation using GROMACS." PLOS ONE 18, no. 8 (August 3, 2023): e0288264. http://dx.doi.org/10.1371/journal.pone.0288264.

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Coarse-grained simulations have emerged as a valuable tool in the study of large and complex biomolecular systems. These simulations, which use simplified models to represent complex biomolecules, reduce the computational cost of simulations and enable the study of larger systems for longer periods of time than traditional atomistic simulations. GROMACS is a widely used software package for performing coarse-grained simulations of biomolecules, and several force fields have been developed specifically for this purpose. In this protocol paper, we explore the advantages of using coarse-grained simulations in the study of biomolecular systems, focusing specifically on simulations performed using GROMACS. We discuss the force fields required for these simulations and the types of research questions that can be addressed using coarse-grained simulations. We also highlight the potential benefits of coarse-grained simulations for the development of new force fields and simulation methodologies. We then discuss the expected results from coarse-grained simulations using GROMACS and the various techniques that can be used to analyze these results. We explore the use of trajectory analysis tools, as well as thermodynamic and structural analysis techniques, to gain insight into the behavior of biomolecular systems.
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Emenecker, Ryan J., Alex S. Holehouse, and Lucia C. Strader. "Biological Phase Separation and Biomolecular Condensates in Plants." Annual Review of Plant Biology 72, no. 1 (June 17, 2021): 17–46. http://dx.doi.org/10.1146/annurev-arplant-081720-015238.

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A surge in research focused on understanding the physical principles governing the formation, properties, and function of membraneless compartments has occurred over the past decade. Compartments such as the nucleolus, stress granules, and nuclear speckles have been designated as biomolecular condensates to describe their shared property of spatially concentrating biomolecules. Although this research has historically been carried out in animal and fungal systems, recent work has begun to explore whether these same principles are relevant in plants. Effectively understanding and studying biomolecular condensates require interdisciplinary expertise that spans cell biology, biochemistry, and condensed matter physics and biophysics. As such, some involved concepts may be unfamiliar to any given individual. This review focuses on introducing concepts essential to the study of biomolecular condensates and phase separation for biologists seeking to carry out research in this area and further examines aspects of biomolecular condensates that are relevant to plant systems.
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Wang, Li, Coucong Gong, Xinzhu Yuan, and Gang Wei. "Controlling the Self-Assembly of Biomolecules into Functional Nanomaterials through Internal Interactions and External Stimulations: A Review." Nanomaterials 9, no. 2 (February 18, 2019): 285. http://dx.doi.org/10.3390/nano9020285.

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Biomolecular self-assembly provides a facile way to synthesize functional nanomaterials. Due to the unique structure and functions of biomolecules, the created biological nanomaterials via biomolecular self-assembly have a wide range of applications, from materials science to biomedical engineering, tissue engineering, nanotechnology, and analytical science. In this review, we present recent advances in the synthesis of biological nanomaterials by controlling the biomolecular self-assembly from adjusting internal interactions and external stimulations. The self-assembly mechanisms of biomolecules (DNA, protein, peptide, virus, enzyme, metabolites, lipid, cholesterol, and others) related to various internal interactions, including hydrogen bonds, electrostatic interactions, hydrophobic interactions, π–π stacking, DNA base pairing, and ligand–receptor binding, are discussed by analyzing some recent studies. In addition, some strategies for promoting biomolecular self-assembly via external stimulations, such as adjusting the solution conditions (pH, temperature, ionic strength), adding organics, nanoparticles, or enzymes, and applying external light stimulation to the self-assembly systems, are demonstrated. We hope that this overview will be helpful for readers to understand the self-assembly mechanisms and strategies of biomolecules and to design and develop new biological nanostructures or nanomaterials for desired applications.
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Smith, Paul E., and B. Montgomery Pettitt. "Modeling Solvent in Biomolecular Systems." Journal of Physical Chemistry 98, no. 39 (September 1994): 9700–9711. http://dx.doi.org/10.1021/j100090a002.

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Rhodes, William. "Coferent dynamics in biomolecular systems." Journal of Molecular Liquids 41 (October 1989): 165–80. http://dx.doi.org/10.1016/0167-7322(89)80076-5.

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Rowe, Rhianon K., and P. Shing Ho. "Relationships between hydrogen bonds and halogen bonds in biological systems." Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials 73, no. 2 (March 29, 2017): 255–64. http://dx.doi.org/10.1107/s2052520617003109.

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The recent recognition that halogen bonding (XB) plays important roles in the recognition and assembly of biological molecules has led to new approaches in medicinal chemistry and biomolecular engineering. When designing XBs into strategies for rational drug design or into a biomolecule to affect its structure and function, we must consider the relationship between this interaction and the more ubiquitous hydrogen bond (HB). In this review, we explore these relationships by asking whether and how XBs can replace, compete against or behave independently of HBs in various biological systems. The complex relationships between the two interactions inform us of the challenges we face in fully utilizing XBs to control the affinity and recognition of inhibitors against their therapeutic targets, and to control the structure and function of proteins, nucleic acids and other biomolecular scaffolds.
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Wang, Yue, Lei Ren, Hongzhen Peng, Linjie Guo, and Lihua Wang. "DNA-Programmed Biomolecular Spatial Pattern Recognition." Chemosensors 11, no. 7 (June 27, 2023): 362. http://dx.doi.org/10.3390/chemosensors11070362.

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Molecular recognition based on non-covalent interactions between two or more molecules plays a crucial role in biological systems. Specific biological molecule recognition has been widely applied in biotechnology, clinical diagnosis, and treatment. The efficiency and affinity of molecular recognition are greatly determined by the spatial conformation of biomolecules. The designability of DNA nanotechnology makes possible the precise programming of the spatial conformation of biomolecules including valency and spacing, further achieving spatial pattern recognition regulation between biomolecules. This review summarizes recent achievements with DNA-based molecular spatial pattern recognition systems, the important factors affecting spatial pattern recognition, and their applications in biosensing, bioimaging, and targeted therapy. The future challenges in and development of this field are discussed and prospected. This review will provide valuable guidance for the creation of new DNA tools to enhance the efficiency and specificity of biomolecular recognition.
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Ren, Pengyu, Jaehun Chun, Dennis G. Thomas, Michael J. Schnieders, Marcelo Marucho, Jiajing Zhang, and Nathan A. Baker. "Biomolecular electrostatics and solvation: a computational perspective." Quarterly Reviews of Biophysics 45, no. 4 (November 2012): 427–91. http://dx.doi.org/10.1017/s003358351200011x.

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AbstractAn understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.
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Dissertations / Theses on the topic "Biomolecular systems"

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Brampton, Christopher. "Forces in biomolecular systems." Thesis, University of Nottingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429077.

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Shah, Rushina(Rushina Jaidip). "Input-output biomolecular systems." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129016.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 194-206).
The ability of cells to sense and respond to their environment is encoded in biomolecular reaction networks, in which information travels through processes such as production, modification, and removal of biomolecules. These reaction networks can be modeled as input-output systems, where the input, state and output variables are concentrations of the biomolecules involved in these reactions. Tools from non-linear dynamics and control theory can be leveraged to analyze and control these systems. In this thesis, we study two key biomolecular networks. In part 1 of this thesis, we study the input-output behavior of signaling systems, which are responsible for the transmission of information both from outside and from within the cells, and are ubiquitous, playing a role in cell cycle progression, survival, growth, differentiation and apoptosis. A signaling pathway transmits information from an upstream system to downstream systems, ideally in a unidirectional fashion.
A key obstacle to unidirectional transmission is retroactivity, the additional reaction flux that affects a system once its species interact with those of downstream systems. In this work, we identify signaling architectures that can overcome retroactivity, allowing unidirectional transmission of signals. These findings can be used to decompose natural signal transduction networks into modules, and at the same time, they establish a library of devices that can be used in synthetic biology to facilitate modular circuit design. In part 2 of this thesis, we design inputs to trigger a transition of cell-fate from one cell type to another. The process of cell-fate decision-making is often modeled by means of multistable gene regulatory networks, where different stable steady states represent distinct cell phenotypes. In this thesis, we provide theoretical results that guide the selection of inputs that trigger a transition, i.e., reprogram the network, to a desired stable steady state.
Our results depend uniquely on the structure of the network and are independent of specific parameter values. We demonstrate these results by means of several examples, including models of the extended network controlling stem-cell maintenance and differentiation.
by Rushina Shah.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineering
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Xin, W. (Weidong). "Continuum electrostatics of biomolecular systems." Doctoral thesis, University of Oulu, 2008. http://urn.fi/urn:isbn:9789514287602.

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Abstract Electrostatic interactions are very important in biomolecular systems. Electrostatic forces have received a great deal of attention due to their long-range nature and the trade-off between desolvation and interaction effects. It remains a challenging task to study and to predict the effects of electrostatic interactions in biomolecular systems. Computer simulation techniques that account for such interactions are an important tool for the study of biomolecular electrostatics. This study is largely concerned with the role of electrostatic interactions in biomolecular systems and with developing novel models to estimate the strength of such interactions. First, a novel formulation based upon continuum electrostatics to compute the electrostatic potential in and around two biomolecules in a solvent with ionic strength is presented. Many, if not all, current methods rely on the (non)linear Poisson-Boltzmann equation to include ionic strength. The present formulation, however, describes ionic strength through the inclusion of explicit ions, which considerably extends its applicability and validity range. The method relies on the boundary element method (BEM) and results in two very similar coupled integral equations valid on the dielectric boundaries of two molecules, respectively. This method can be employed to estimate the total electrostatic energy of two protein molecules at a given distance and orientation in an electrolyte solution with zero to moderately high ionic strength. Secondly, to be able to study interactions between biomolecules and membranes, an alternative model partly based upon the analytical continuum electrostatics (ACE) method has been also formulated. It is desirable to develop a method for calculating the total solvation free energy that includes both electrostatic and non-polar energies. The difference between this model and other continuum methods is that instead of determining the electrostatic potential, the total electrostatic energy of the system is calculated by integrating the energy density of the electrostatic field. This novel approach is employed for the calculation of the total solvation free energy of a system consisting of two solutes, one of which could be an infinite slab representing a membrane surface.
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Janosi, Lorant. "Multiscale modeling of biomolecular systems." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4801.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on February 14, 2008) Vita. Includes bibliographical references.
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Desai, Amruta. "Design support for biomolecular systems." Cincinnati, Ohio : University of Cincinnati, 2010. http://rave.ohiolink.edu/etdc/view.cgi?acc_num=ucin1265986863.

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Thesis (M.S.)--University of Cincinnati, 2010.
Advisor: Carla Purdy. Title from electronic thesis title page (viewed Apr. 19, 2010). Includes abstract. Keywords: Biological pathways; weighted gate; BMDL; pyrimidine. Includes bibliographical references.
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Diez, Stefan, and Jonathon Howard. "Nanotechnological applications of biomolecular motor systems." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2008. http://nbn-resolving.de/urn:nbn:de:bsz:14-ds-1223724473713-41365.

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Neuerliche Fortschritte im Verständnis biomolekularer Motoren rücken ihre Anwendung als Nanomaschinen in den Bereich des Möglichen. So könnten sie zum Beispiel als Nanoroboter arbeiten, um in molekularen Fabriken kleine – aber dennoch komplizierte – Strukturen auf winzigen Förderbändern herzustellen, um Netzwerke molekularer Nanodrähte und Transistoren für elektronische Anwendungen zu assemblieren oder sie könnten in adaptiven Materialien patrouillieren und diese, wenn nötig, reparieren. In diesem Sinne besitzen biomolekulare Motoren das Potenzial, die Basis für die Konstruktion, Strukturierung und Wartung nanoskaliger Materialien zu bilden
Recent advances in understanding how biomolecular motors work have raised the possibility that they might find applications as nanomachines. For example, they could be used as molecule- sized robots that work in molecular factories where small, but intricate structures are made on tiny assembly lines, that construct networks of molecular conductors and transistors for use as electrical circuits, or that continually patrol inside “adaptive” materials and repair them when necessary. Thus biomolecular motors could form the basis of bottom-up approaches for constructing, active structuring and maintenance at the nanometer scale
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Dey, Abhishek. "Modeling and identification of biomolecular systems." Thesis, IIT Delhi, 2019. http://eprint.iitd.ac.in:80//handle/2074/8121.

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Tyka, Michael. "Absolute free energy calculations for biomolecular systems." Thesis, University of Bristol, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439666.

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Shu, Wenmiao. "Biomolecular sensing and actuation using microcantilever systems." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612828.

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Lickert, Benjamin [Verfasser], and Gerhard [Akademischer Betreuer] Stock. "Data-based Langevin modeling of biomolecular systems." Freiburg : Universität, 2021. http://d-nb.info/1241962669/34.

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Books on the topic "Biomolecular systems"

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van Gunsteren, Wilfred F., Paul K. Weiner, and Anthony J. Wilkinson, eds. Computer Simulation of Biomolecular Systems. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-017-1120-3.

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García Gómez-Tejedor, Gustavo, and Martina Christina Fuss, eds. Radiation Damage in Biomolecular Systems. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2564-5.

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Christina, Fuss Martina, and SpringerLink (Online service), eds. Radiation Damage in Biomolecular Systems. Dordrecht: Springer Netherlands, 2012.

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Rizzarelli, E., and T. Theophanides, eds. Chemistry and Properties of Biomolecular Systems. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3620-4.

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Russo, N., J. Anastassopoulou, and G. Barone, eds. Properties and Chemistry of Biomolecular Systems. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0822-5.

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Vasilescu, D., J. Jaz, L. Packer, and B. Pullman, eds. Water and Ions in Biomolecular Systems. Basel: Birkhäuser Basel, 1990. http://dx.doi.org/10.1007/978-3-0348-7253-9.

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Ryabov, Artem. Stochastic Dynamics and Energetics of Biomolecular Systems. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27188-0.

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1938-, Beveridge David L., Jorgensen William L, and New York Academy of Sciences., eds. Computer simulation of chemical and biomolecular systems. New York, N.Y: New York Academy of Sciences, 1986.

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Rui-Sheng, Wang, and Zhang Xiang-Sun 1943-, eds. Biomolecular networks: Methods and applications in systems biology. Hoboken, N.J: Wiley, 2009.

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J, Wilkinson Anthony, Gunsteren Wilfred F. van, and Weiner Paul K, eds. Computer simulation of biomolecular systems: Theoretical and experimental applications. Dordrecht: Kluwer, 1997.

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Book chapters on the topic "Biomolecular systems"

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Solov’yov, Ilia A., Andrey V. Korol, and Andrey V. Solov’yov. "Biomolecular Systems." In Multiscale Modeling of Complex Molecular Structure and Dynamics with MBN Explorer, 171–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56087-8_5.

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Chandran, Harish, Sudhanshu Garg, Nikhil Gopalkrishnan, and John H. Reif. "Biomolecular Computing Systems." In Biomolecular Information Processing, 199–223. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527645480.ch11.

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Vasilescu, D., and H. Kranck. "Noise in Biomolecular Systems." In Modern Bioelectrochemistry, 397–430. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2105-7_14.

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Fernández Stigliano, Ariel. "Multitarget Control of Drug Impact: A Therapeutic Imperative in Cancer Systems Biology." In Biomolecular Interfaces, 285–309. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16850-0_13.

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Strack, Guinevere, Heather R. Luckarift, Glenn R. Johnson, and Evgeny Katz. "Information Security Applications Based on Biomolecular Systems." In Biomolecular Information Processing, 103–16. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527645480.ch6.

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Wilson, Ian D., and Jeremy K. Nicholson. "Chapter 12. Metabonomics and Global Systems Biology." In RSC Biomolecular Sciences, 295–316. Cambridge: Royal Society of Chemistry, 2007. http://dx.doi.org/10.1039/9781847558107-00295.

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Fernández Stigliano, Ariel. "Wrapping Drug Combinations for Therapeutic Editing of Side Effects: Systems Biology Meets Wrapping Technology." In Biomolecular Interfaces, 259–84. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16850-0_12.

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Chalikian, Tigran V., and Robert B. Macgregor. "Volumetric Properties of Biomolecular Systems." In Encyclopedia of Biophysics, 1–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-642-35943-9_10071-1.

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Ciobanu, Gabriel. "Software Verification of Biomolecular Systems." In Natural Computing Series, 39–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18734-6_3.

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Katz, Evgeny. "Bioelectronic Devices Controlled by Enzyme-Based Information Processing Systems." In Biomolecular Information Processing, 61–80. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527645480.ch4.

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Conference papers on the topic "Biomolecular systems"

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Arbon, Robert E., Alex J. Jones, Lars A. Bratholm, Tom Mitchell, and David R. Glowacki. "Sonifying Stochastic Walks on Biomolecular Energy Landscapes." In The 24th International Conference on Auditory Display. Arlington, Virginia: The International Community for Auditory Display, 2018. http://dx.doi.org/10.21785/icad2018.032.

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Translating the complex, multi-dimensional data produced by simulations of biomolecules into an intelligible form is a major challenge in computational chemistry and biology. The so-called “free energy landscape” is amongst the most fundamental concepts used by scientists to understand both static and dynamic properties of biomolecular systems. In this paper we use Markov models to design a strategy for mapping features of this landscape to sonic parameters, for use in conjunction with visual display techniques such as structural animations and free energy diagrams. This allows for concurrent visual display of the physical configuration of a biomolecule and auditory display of characteristics of the corresponding free energy landscape. The resulting sonification provides information about the relative free energy features of a given configuration including its stability.
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Nguyen, Mary-Anne, and Andy Sarles. "Microfabrication for Packaged Biomolecular Unit Cells." In ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/smasis2013-3068.

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This paper focuses on developing a closed fluidic environment for packaging biomolecular unit cells, which consists of a synthetic lipid bilayer and other biomolecules contained in a near solid-state material with two regions that contain hydrophobic oil (i.e. nonpolar solvent) surrounding aqueous droplets. This research provides a stepping-stone towards an autonomic biomolecular material system, whereby a packaged system will allow for precise droplet interface bilayer (DIB) formation without the interference of outside contamination for long-term applications. Also, substrate materials need to maintain droplets and preserve the self-assembly and stimuli-responsive properties of biomolecules within the unit cell. A critical feature of an encapsulating material is that it does not absorb either of the liquid phases required to form DIBs. Oil depletion tests within sealed, polymeric substrates show that polydimethylsiloxane (PDMS) absorbs full volume of injected hexadecane in approximately 27 hours. However, polyurethane substrates maintain the original amount of oil injected even after several weeks. Bilayer lifetime is also monitored within an environment in which the oil is also depleting. The results of this test show the longevity of a DIB to be shorter than oil lifetime. The lipid-encased droplets disconnect after approximately 10 hours, when there is only approximately <60% amount of oil present. In addition, an initial microfluidic substrate is designed such that a single T-junction intersection can be used to form monodisperse droplets within a primary oil-filled channel and a downstream increase in channel width can be used to connect droplets to form DIBs.
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Madden(, Paul A., James Penman, and Ettore Fois. "Ab Initio Molecular Dynamics Applied to Molecular Systems." In Advances in biomolecular simulations. AIP, 1991. http://dx.doi.org/10.1063/1.41316.

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van Gunsteren, W. F. "Computer Simulation of Biomolecular Systems: Overview of Time-Saving Techniques." In Advances in biomolecular simulations. AIP, 1991. http://dx.doi.org/10.1063/1.41334.

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Haring Bolivar, Peter G. "Biomolecular Sensing with Integrated THz Systems." In Optical Terahertz Science and Technology. Washington, D.C.: OSA, 2005. http://dx.doi.org/10.1364/otst.2005.wb1.

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Aizawa, Masuo, T. Niimi, T. Haruyama, and E. Kobatake. "Design of environment-responsive biomolecular systems." In 1996 Symposium on Smart Structures and Materials, edited by Andrew Crowson. SPIE, 1996. http://dx.doi.org/10.1117/12.232133.

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Freeman, Eric C., Michael K. Philen, and Donald J. Leo. "Principles of Biomolecular Network Design." In ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/smasis2013-3113.

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Networks of biomolecular unit cells are proposed as a new type of biologically inspired intelligent materials. These materials are derived from natural cellular mechanics and aim to improve current biologically-inspired technologies by recreating the desired systems from the basic building block of the natural world; the cell. The individual biomolecular unit cell is able to replicate natural cellular abilities through a combination of lipid bilayer membranes containing embedded proteins and peptides. While individual unit cells offer an ideal testing environment for demonstrating proofs of concept, more advanced abilities require larger networks, utilizing cell-to-cell interactions. The cell-to-cell interactions often involve multiple modes of communication, which have been identified for this paper as primarily electrical, chemical, and mechanical phenomenon. Previous modeling efforts have incorporated the electrical portion through equivalent circuit models, but these lack the ability to fully explain some of the network characteristics. A new formulation is presented here to illustrate how these three classes of phenomenon may be coupled to achieve various engineering design goals.
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Liu, Tse-Yen, I.-Shun Wang, Pei-Wen Yen, Shiang-Chi Lin, Kuan-Chou Lin, Jhu-Siang Jheng, Da-Yuan Chang, and Chih-Ting Lin. "CMOS-based biomolecular diagnosis platform." In 2017 IEEE 12th International Conference on Nano/Micro Engineered and Molecular Systems (NEMS). IEEE, 2017. http://dx.doi.org/10.1109/nems.2017.8016982.

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Jiang, Hua, Marc D. Riedel, and Keshab K. Parhi. "Digital signal processing with biomolecular reactions." In 2010 IEEE Workshop On Signal Processing Systems (SiPS). IEEE, 2010. http://dx.doi.org/10.1109/sips.2010.5624796.

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Tamba, Masaaki, and Takashi Nakakuki. "Renewable implementation of rational biomolecular systems design." In 2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). IEEE, 2020. http://dx.doi.org/10.23919/sice48898.2020.9240329.

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Reports on the topic "Biomolecular systems"

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Beebe, David J. An Advanced Platform for Biomolecular Detection and Analysis Systems. Fort Belvoir, VA: Defense Technical Information Center, February 2005. http://dx.doi.org/10.21236/ada432950.

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Bachand, George David, and Amanda Carroll-Portillo. Engineering intracellular active transport systems as in vivo biomolecular tools. Office of Scientific and Technical Information (OSTI), November 2006. http://dx.doi.org/10.2172/899371.

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Clark, Douglas S. Performance-Enhancing Biomolecular Treatment Strategies for Naval Graywater Filtration Systems. Fort Belvoir, VA: Defense Technical Information Center, March 2002. http://dx.doi.org/10.21236/ada399945.

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Hummer, G., A. E. Garcia, and D. M. Soumpasis. Potential-of-mean-force description of ionic interactions and structural hydration in biomolecular systems. Office of Scientific and Technical Information (OSTI), October 1994. http://dx.doi.org/10.2172/10186924.

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Moore, Jeff, Hassan Aref, Ron Adrian, Deborah Leckband, and David J. Beebe. Engineering Solutions for Robust and Efficient Microfluidic Biomolecular Systems: Mixing, Fabrication, Diagnostics, Modeling, Antifouling and Functional Materials. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada411413.

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Roux, B., Y. Luo, and W. Jiang. NAMD - The Engine for Large-Scale Classical MD Simulations of Biomolecular Systems Based on a Polarizable Force Field: ALCF-2 Early Science Program Technical Report. Office of Scientific and Technical Information (OSTI), May 2013. http://dx.doi.org/10.2172/1079771.

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Rodriguez Muxica, Natalia. Open configuration options Bioinformatics for Researchers in Life Sciences: Tools and Learning Resources. Inter-American Development Bank, February 2022. http://dx.doi.org/10.18235/0003982.

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The COVID-19 pandemic has shown that bioinformatics--a multidisciplinary field that combines biological knowledge with computer programming concerned with the acquisition, storage, analysis, and dissemination of biological data--has a fundamental role in scientific research strategies in all disciplines involved in fighting the virus and its variants. It aids in sequencing and annotating genomes and their observed mutations; analyzing gene and protein expression; simulation and modeling of DNA, RNA, proteins and biomolecular interactions; and mining of biological literature, among many other critical areas of research. Studies suggest that bioinformatics skills in the Latin American and Caribbean region are relatively incipient, and thus its scientific systems cannot take full advantage of the increasing availability of bioinformatic tools and data. This dataset is a catalog of bioinformatics software for researchers and professionals working in life sciences. It includes more than 300 different tools for varied uses, such as data analysis, visualization, repositories and databases, data storage services, scientific communication, marketplace and collaboration, and lab resource management. Most tools are available as web-based or desktop applications, while others are programming libraries. It also includes 10 suggested entries for other third-party repositories that could be of use.
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Reichert, D. E., and P. J. A. Kenis. Microfluidic Radiometal Labeling Systems for Biomolecules. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1032377.

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Doktycz, M. J. Dual Manifold System for Arraying Biomolecules. Office of Scientific and Technical Information (OSTI), April 2001. http://dx.doi.org/10.2172/814531.

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Doktycz, M. J. CRADA Final Report-Dual Manifold System for Arraying Biomolecules. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/814372.

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