Relevant bibliographies by topics / Molecular Computation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Molecular Computation'

Author: Grafiati
Published: 5 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Molecular Computation"

1

FREEMANTLE, MICHAEL. "MOLECULAR COMPUTATION." Chemical & Engineering News 78, no. 18 (2000): 12. http://dx.doi.org/10.1021/cen-v078n018.p012.

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Potter, Aneirin. "044 At what resolution does the brain perform computations?" Journal of Neurology, Neurosurgery & Psychiatry 93, no. 9 (2022): e2.239. http://dx.doi.org/10.1136/jnnp-2022-abn2.88.

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Computation is the transformation of inputs into outputs through logical operations such as AND, OR, and NOT. This literature review compares models of computation at different physiological resolutions, whole brain networks, multi-cell circuits, individual synapses and individual molecular interactions and discusses if these models might be useful for bridging between functional neuroimaging with molecular models of disease. While resolution in functional neuroimaging such as EEG, MEG, PET, and fMRI is of groups of neurons pharmacotherapy alters the brain at a molecular level. Bridging this r
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Sarpeshkar, R. "Analog synthetic biology." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2012 (2014): 20130110. http://dx.doi.org/10.1098/rsta.2013.0110.

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We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic an
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Larsen, Brett W., and Shaul Druckmann. "Towards a more general understanding of the algorithmic utility of recurrent connections." PLOS Computational Biology 18, no. 6 (2022): e1010227. http://dx.doi.org/10.1371/journal.pcbi.1010227.

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Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation”
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De Silva, A. P. "Molecular computation: Molecular logic gets loaded." Nature Materials 4, no. 1 (2005): 15–16. http://dx.doi.org/10.1038/nmat1301.

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Connolly, Michael L. "Computation of molecular volume." Journal of the American Chemical Society 107, no. 5 (1985): 1118–24. http://dx.doi.org/10.1021/ja00291a006.

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Stemmer, W. P. C. "The Evolution of Molecular Computation." Science 270, no. 5241 (1995): 1510. http://dx.doi.org/10.1126/science.270.5241.1510.

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Gehani, Ashish, and John Reif. "Micro flow bio-molecular computation." Biosystems 52, no. 1-3 (1999): 197–216. http://dx.doi.org/10.1016/s0303-2647(99)00048-9.

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Gaita-Ariño, A., F. Luis, S. Hill, and E. Coronado. "Molecular spins for quantum computation." Nature Chemistry 11, no. 4 (2019): 301–9. http://dx.doi.org/10.1038/s41557-019-0232-y.

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Sam Lemonick. "Largest molecular quantum computation performed." C&EN Global Enterprise 98, no. 33 (2020): 8. http://dx.doi.org/10.1021/cen-09833-scicon6.

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Dissertations / Theses on the topic "Molecular Computation"

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Rohlfshagen, Philipp. "Molecular Algorithms for Evolutionary Computation." Thesis, University of Birmingham, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.522032.

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Deng, Wei-Qiao Kuppermann Aron. "Computation aided design in molecular nanotechnology /." Diss., Pasadena, Calif. : California Institute of Technology, 2004. http://resolver.caltech.edu/CaltechETD:etd-05282004-161503.

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Rachinger, Christoph. "Scalable Computation of Long-Range Potentialsfor Molecular Dynamics." Thesis, KTH, Numerisk analys, NA, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-124321.

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To calculate long-range potentials in a molecular dynamics simulation, a naive approach using direct particle interactions needs a computational work of order O(N2). This is infeasible for larger simulations. In order to reduce this complexity and thus allow to increase the size of the simulation, several algorithms have been proposed in the last decades. This thesis first gives an overview over these algorithms and examines the advantages and disadvantages of these methods with respect to high performance computing, i.e., how well they are suited for a good scalability on a many-processor sys
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Drexler, K. Eric. "Molecular machinery and manufacturing with applications to computation." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/27999.

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McClean, Jarrod Ryan. "Algorithms Bridging Quantum Computation and Chemistry." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:17467376.

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The design of new materials and chemicals derived entirely from computation has long been a goal of computational chemistry, and the governing equation whose solution would permit this dream is known. Unfortunately, the exact solution to this equation has been far too expensive and clever approximations fail in critical situations. Quantum computers offer a novel solution to this problem. In this work, we develop not only new algorithms to use quantum computers to study hard problems in chemistry, but also explore how such algorithms can help us to better understand and improve our tradition
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Temelso, Berhane. "Computation of Molecular Properties at the Ab Initio Limit." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14638.

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The accuracy of a quantum chemical calculation inherently depends on the ability to account for the completeness of the one- and n-particle spaces. The size of the basis set used can be systematically increased until it reaches the complete one-particle basis set limit (CBS) while the n-particle space approaches its exact full configuration interaction (FCI) limit by following a hierarchy of electron correlation methods developed over the last seventy years. If extremely high accuracy is desired, properly correcting for very small effects such as those resulting the Born-Oppenheimer approximati
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Chandramoorthy, Nisha. "Molecular dynamics-based approaches for mesoscale lubrication." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107059.

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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 101-109).<br>Classical lubrication theory is unable to describe nanoscale flows due to the failure of two of its constitutive components: a) the Newtonian stress-strain rate relationship and b) the no-slip boundary condition. In this thesis, we present a methodology for deriving a modified Reynolds equation (referred to as the Molecular Dynamics-based Equation for Lubrication, or the MODEL) which overc
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Mommers, Cornelis Johannes Gerardus. "Universal Quantum Computation Using Discrete Holonomies." Thesis, Uppsala universitet, Materialteori, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444209.

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Harris, Michael James. "Biased sampling methods for free energy computation with molecular dynamics simulations." abstract and full text PDF (free order & download UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1453582.

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Rival, Olivier. "Organic materials for quantum computation." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:3674b9ce-c284-47b5-ab0d-76d094c849f0.

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Quantum mechanics has a long history of helping computer science. For a long time, it provided help only at the hardware level by giving a better understanding of the properties of matter and thus allowing the design of ever smaller and ever more efficient components. For the last few decades, much research has been dedicated to finding whether one can change computer science even more radically by using the principles of quantum mechanics at both the hardware and algorithm levels. This field of research called Quantum Information Processing (QIP) has rapidly seen interesting theoretical devel
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Books on the topic "Molecular Computation"

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1953-, Gheorghe Marian, ed. Molecular computation models: Unconventional approaches. Idea Group Pub., 2005.

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Amusia, Miron Ya, and Larissa V. Chernysheva. Computation of Atomic and Molecular Processes. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85143-9.

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Drexler, K. Eric. Nanosystems: Molecular machinery, manufacturing and computation. Wiley, 1992.

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Drexler, K. Eric. Nanosystems: Molecular machinery, manufacturing, and computation. Wiley, 1992.

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Tino, Gramss, ed. Non-standard computation: Molecular computation, cellular automata, evolutionary algorithms, quantum computers. Wiley-VCH, 1998.

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1954-1996, Cuthbertson Roy, Holcombe, W. M. L. 1944-, Paton Ray, and International Workshop on Information Processing in Cells and Tissues (1st : 1995 : Liverpool, England), eds. Computation in cellular and molecular biological systems. World Scientific, 1996.

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Horst, Köppel, ed. Conical intersections: Theory, computation and experiment. World Scientific, 2011.

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Yarkony, David, and Wolfgang Domcke. Conical intersections: Theory, computation and experiment. Edited by Köppel Horst. World Scientific, 2011.

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MacLennan, Bruce J. Field computation and nonpropositional knowledge. Naval Postgraduate School, 1987.

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1959-, Merz Kenneth M., and Roux Benoît 1958-, eds. Biological membranes: A molecular perspective from computation and experiment. Birkhauser Boston, 1996.

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Book chapters on the topic "Molecular Computation"

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Groß, Michael. "Molecular Computation." In Non-Standard Computation. Wiley-VCH Verlag GmbH & Co. KGaA, 2005. http://dx.doi.org/10.1002/3527602968.ch2.

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Juarez-Martinez, Gabriela, Alessandro Chiolerio, Paolo Allia, et al. "Molecular Computation." In Encyclopedia of Nanotechnology. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-90-481-9751-4_100453.

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Pei, Renjun. "Deoxyribozyme-Based Molecular Computation." In DNA Nanotechnology. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36077-0_17.

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Braun, Jasper, Daniel Cruz, and Nataša Jonoska. "Platform Color Designs for Interactive Molecular Arrangements." In Unconventional Computation and Natural Computation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58187-3_6.

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Castellanos, J., S. Leiva, J. Rodrigo, and A. Rodríguez-Patón. "Molecular Computation for Genetic Algorithms." In Rough Sets and Current Trends in Computing. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69115-4_13.

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Kari, Lila, Jarkko Kari, and Laura F. Landweber. "Reversible Molecular Computation in Ciliates." In Jewels are Forever. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60207-8_31.

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Landweber, Laura F., and Lila Kari. "Universal Molecular Computation in Ciliates." In Natural Computing Series. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-55606-7_13.

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Li, Xiuting, Laisheng Xiang, and Xiyu Liu. "Enterprise Evolution with Molecular Computation." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7618-0_92.

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Katoh, Naoki. "A Proof of the Molecular Conjecture." In Algorithms and Computation. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10631-6_2.

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Pickup, B. T. "Theory and Computation of Molecular Properties." In Atomic and Molecular Properties. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-1639-6_3.

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Conference papers on the topic "Molecular Computation"

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Aubert-Kato, Nathanael, and Mika Ito. "Exploration of Reservoir Properties in Molecular Computing Systems." In 2024 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2024. http://dx.doi.org/10.1109/cec60901.2024.10612038.

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Sun, Jinyuan, Auston Li, Yifan Deng, and Jiabo Li. "ChatMol Copilot: An Agent for Molecular Modeling and Computation Powered by LLMs." In Proceedings of the 1st Workshop on Language + Molecules (L+M 2024). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.langmol-1.7.

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Cerveira, Arthur, Frederico Kremer, Darling Lourenço, and Ulisses B. Corrêa. "Evaluation Framework for AI -driven Molecular Design of Multi-target Drugs: Brain Diseases as a Case Study." In 2024 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2024. http://dx.doi.org/10.1109/cec60901.2024.10611839.

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Reif, John H. "Parallel molecular computation." In the seventh annual ACM symposium. ACM Press, 1995. http://dx.doi.org/10.1145/215399.215446.

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Kuroda, Takayoshi. "MOLECULAR MAGNETS FOR QUANTUM COMPUTATION." In Molecular Realizations of Quantum Computing 2007. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789812838681_0006.

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Jiang, Hua, Marc D. Riedel, and Keshab K. Parhi. "Asynchronous computation with molecular reactions." In 2011 45th Asilomar Conference on Signals, Systems and Computers. IEEE, 2011. http://dx.doi.org/10.1109/acssc.2011.6190049.

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Fujii, Teruo. "Drawing Feature Maps of Molecular Computation." In 2021 21st International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers). IEEE, 2021. http://dx.doi.org/10.1109/transducers50396.2021.9495654.

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Jiang, Hua, Marc Riedel, and Keshab Parhi. "Synchronous sequential computation with molecular reactions." In the 48th Design Automation Conference. ACM Press, 2011. http://dx.doi.org/10.1145/2024724.2024911.

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BAI, PING, SHUO-WANG YANG, PING WU, and ER-PING LI. "MOLECULES AND STRUCTURES FOR MOLECULAR ELECTRONIC NANODEVICES." In Proceedings of the International Conference on Scientific and Engineering Computation (IC-SEC) 2002. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2002. http://dx.doi.org/10.1142/9781860949524_0018.

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Hornkohl, J. O., C. Parigger, and J. W. L. Lewis. "Computation of Synthetic Diatomic Spectra." In Laser Applications to Chemical Analysis. Optica Publishing Group, 1994. http://dx.doi.org/10.1364/laca.1994.fa.5.

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Comparisons of measured spectra to synthetic spectra have become commonplace in both pure and applied spectroscopy. For example, the comparison might be made as part of the evaluation of the accuracy of the molecular parameters, or the comparison might be made for determination of the temperature or population density of the spectroscopically active molecule. Numerous computer programs have been written for the computation of synthetic diatomic spectra. Many of these apply only to a specific type of transition. Some apply only to specific bands of a certain molecule. One starting on a new mole
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Reports on the topic "Molecular Computation"

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J. BERG, C. BURNS, and ET AL. ACTINIDE MOLECULAR SCIENCE: F-ELECTRONIC STRUCTURE IN SYNTHESIS, SPECTROSCOPY, AND COMPUTATION. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/772849.

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Di Felice, Rosa, Anna Krylov, Itay Hen, Amir Kalev, Marco Fornari, and Marco Buongiorno Nardelli. Q4Q: Quantum Computation for Quantum Prediction of Materials and Molecular Properties. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2281191.

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Politzer, Peter, Monica C. Concha, and Pat Lane. Computational Investigation of the Stabilities of Some Proposed Molecules and Molecular-Anions. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada345530.

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Brandt, Achi. Multiscale Computational Methods in Molecular Simulations. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada407040.

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Felmy, Andrew R., Eric J. Bylaska, David A. Dixon, et al. Computational Studies in Molecular Geochemistry and Biogeochemistry. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/881689.

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Hill, 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, 2021. http://dx.doi.org/10.61092/iaea.25ex-cn8n.

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The International Code Centres Network (CCN) is a group of experts developing codes and models for atomic, molecular and plasma-surface interaction data relevant to fusion applications. Variable subsets of the group are brought together by the IAEA Atomic and Molecular Data (AMD) Unit in order to discuss computational and scientific issues associated with code developments. At the 7th Technical Meeting described in this report, which was held virtually from 18 – 20 October 2021, 18 experts in the field of Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations of radiation dama
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Rzhetsky, Andrey, and Dimitris Anastassiou. COMPUTATIONAL ANALYSIS AND SIMULATION OF BACTERIAL MOLECULAR NETWORKS. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/968434.

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Hill, Christian. International Atomic and Molecular Code Centres Network: Virtual Atomic and Molecular Data Centres Consortium Annual Meeting. International Atomic Energy Agency, 2023. http://dx.doi.org/10.61092/iaea.s57n-ra6p.

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The International Code Centres Network (CCN) is a group of experts developing codes and models for atomic, molecular and plasma-surface interaction data relevant to fusion applications. Variable subsets of the group are brought together by the IAEA Atomic and Molecular Data (AMD) Unit in order to discuss computational and scientific issues associated with code developments. At the 8th Technical Meeting described in this report, which was held virtually from 15 – 17 November 2023, 31 experts in the field of atomic and molecular physics met, representing 23 databases within the Virtual Atomic an
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Basak, Subnash C. Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada374363.

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Oskolkov, Nikolay. Clustering High-Dimensional Data. Instats Inc., 2024. http://dx.doi.org/10.61700/sdtam1p82ak2m1574.

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This seminar on 'Clustering High-Dimensional Data,' led by Nikolay Oskolkov from Molecular Biosciences at Lund University, provides comprehensive training in clustering techniques using R and Python. Participants will learn to manage high-dimensional datasets, apply various clustering algorithms, and evaluate their performance to enhance their research capabilities in fields such as bioinformatics and computational biology.
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