Relevant bibliographies by topics / DNA model

Contents

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

Academic literature on the topic 'DNA model'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "DNA model"

1

Frank-Kamenetskii, M. D., V. V. Anshelevich, and A. V. Lukashin. "Polyelectrolyte model of DNA." Uspekhi Fizicheskih Nauk 151, no. 4 (1987): 595. http://dx.doi.org/10.3367/ufnr.0151.198704b.0595.

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Handelsman, Jo. "Call for Papers: Unique Model Systems." DNA and Cell Biology 27, no. 6 (June 2008): 287. http://dx.doi.org/10.1089/dna.2008.1504.

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Frank-Kamenetskiĭ, M. D., V. V. Anshelevich, and A. V. Lukashin. "Polyelectrolyte model of DNA." Soviet Physics Uspekhi 30, no. 4 (April 30, 1987): 317–30. http://dx.doi.org/10.1070/pu1987v030n04abeh002833.

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Davies, S. W., and D. A. Seale. "DNA Microarray Stochastic Model." IEEE Transactions on Nanobioscience 4, no. 3 (September 2005): 248–54. http://dx.doi.org/10.1109/tnb.2005.853665.

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Middleton, James. "Handy DNA Nucleotide Model." American Biology Teacher 81, no. 3 (March 1, 2019): 193–96. http://dx.doi.org/10.1525/abt.2019.81.3.193.

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A readily available resource to create a model for the study of DNA is the human hand. Students can recognize how structure and function of nucleotides determine structure and function of the DNA molecule by labeling parts of a gloved hand with the parts of a DNA molecule.
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Alireza, Sepehri, Shoorvazi Somayyeh, and Moradi Marjaneh Aliakbar. "Calculating the Specific Heat of DNA by using Phononic Model." Greener Journal of Biological Sciences 3, no. 5 (July 13, 2013): 187–91. http://dx.doi.org/10.15580/gjbs.2013.5.051613617.

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Kelchner, Scot A. "Phylogenetic models and model selection for noncoding DNA." Plant Systematics and Evolution 282, no. 3-4 (July 30, 2008): 109–26. http://dx.doi.org/10.1007/s00606-008-0071-6.

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XU, Jin, and Yue-Ke FAN. "Classical Ramsey Number DNA Computing Model (Ⅱ): Add-Bit-Sequence DNA computing Model." Chinese Journal of Computers 31, no. 12 (October 16, 2009): 2081–89. http://dx.doi.org/10.3724/sp.j.1016.2008.02081.

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ZHAO, YUQI, and HOWARD B. LIEBERMAN. "Schizosaccharomyces pombe:A Model for Molecular Studies of Eukaryotic Genes." DNA and Cell Biology 14, no. 5 (May 1995): 359–71. http://dx.doi.org/10.1089/dna.1995.14.359.

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Mohamad, Abdul Adheem, and Tsukasa Yashiro. "A TOPOLOGICAL MODEL OF DNA REPLICATION WITH DNA-LINKS." Far East Journal of Mathematical Sciences (FJMS) 107, no. 1 (September 27, 2018): 241–55. http://dx.doi.org/10.17654/ms107010241.

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Dissertations / Theses on the topic "DNA model"

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高銘謙 and Ming-him Ko. "A multi-agent model for DNA analysis." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31222778.

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Ko, Ming-him. "A multi-agent model for DNA analysis /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21949116.

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Luchetti, Andrea <1976&gt. "Evolution of repetitive DNA in model arthropods." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/338/.

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Friedrich, Tomáš. "Komprese DNA sekvencí." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237222.

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The increasing volume of biological data requires finding new ways to save these data in genetic banks. The target of this work is design and implementation of a novel algorithm for compression of DNA sequences. The algorithm is based on aligning DNA sequences agains a reference sequence and storing only diferencies between sequence and reference model. The work contains basic prerequisities from molecular biology which are needed for understanding of algorithm details. Next aligment algorithms and common compress schemes suitable for storing of diferencies agains reference sequence are descri
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Santos, Elmer Buluran. "Biologic response to papillomavirus DNA in COPV model." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621132.

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Arredondo, Ryan. "Properties of Graphs Used to Model DNA Recombination." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/4979.

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A model for DNA recombination uses 4-valent rigid vertex graphs, called assembly graphs. An assembly graph, similarly to the projection of knots, can be associated with an unsigned Gauss code, or double occurrence word. We define biologically motivated reductions that act on double occurrence words and, in turn, on their associated assembly graphs. For every double occurrence word w there is a sequence of reduction operations that may be applied to w so that what remains is the empty word, [epsilon]. Then the nesting index of a word w, denoted by NI(w), is defined to to be the least number of
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Darko, Janice. "Fluorescent Labeling of Antibiotic Resistant Bacteria Model DNA." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7600.

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Global threats to treatment of bacterial infections due to antibiotic resistance (AR) have been on the rise in recent years. Current diagnostic tests identify bacteria by using blood culture, which takes more than 24 hours. This study focuses on the fluorescent labeling of DNA derived from bacterial AR genes (KPC & VIM) and other model DNAs using oligreen dye (OG) and molecular beacons (MB). A NanoDrop 3300 fluorospectrometer was used to take fluorescence measurements. Linear dynamic range and labeling efficiency were dependent on the following optimized conditions: dilution factor of OG (200
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Allegrini, Paolo. "Model for Long-range Correlations in DNA Sequences." Thesis, University of North Texas, 1996. https://digital.library.unt.edu/ark:/67531/metadc279189/.

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We address the problem of the DNA sequences developing a "dynamical" method based on the assumption that the statistical properties of DNA paths are determined by the joint action of two processes, one deterministic, with long-range correlations, and the other random and delta correlated. The generator of the deterministic evolution is a nonlinear map, belonging to a class of maps recently tailored to mimic the processes of weak chaos responsible for the birth of anomalous diffusion. It is assumed that the deterministic process corresponds to unknown biological rules which determine the DNA pa
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Tello, Cajiao John James 1990. "The influence of the DNA conformation on the radiation-induced DNA damage probabilities = A influência da conformação do DNA nas probabilidades de dano induzido por radiações." [s.n.], 2016. http://repositorio.unicamp.br/jspui/handle/REPOSIP/305738.

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Orientador: Mario Antonio Bernal Rodriguez<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin<br>Made available in DSpace on 2018-08-30T22:42:12Z (GMT). No. of bitstreams: 1 TelloCajiao_JohnJames_M.pdf: 2614936 bytes, checksum: e5bdfc91b42434b003cad0b5fa850afb (MD5) Previous issue date: 2016<br>Resumo: O objetivo deste trabalho é estudar a influência da conformação do DNA na probabilidade de dano direto produzido por partículas ionizantes. Além disso, os fundamentos mecanicísticos do modelo Linear-Quadrático são investigadas através de um modelo
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Lee, Kyeong Eun. "Bayesian models for DNA microarray data analysis." Diss., Texas A&M University, 2005. http://hdl.handle.net/1969.1/2465.

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Selection of signi?cant genes via expression patterns is important in a microarray problem. Owing to small sample size and large number of variables (genes), the selection process can be unstable. This research proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent variables in a regression setting and use a Bayesian mixture prior to perform the variable selection. Due to the binary nature of the data, the posterior distributions of the parameters are not in explicit form, and we need to use a combination of truncated sampling and Markov Chain Monte Carlo (MCMC)
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Books on the topic "DNA model"

1

Sakalosky, G. P. The predictor model. Gatlinburg, TN: Grams Communications Publication, 1992.

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Rintala, Anne C. DNA repair in a radioresistant breast cancer model system. Sudbury, Ont: Laurentian University, 2000.

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Snapka, Robert M. The SV40 replicon model for analysis of anticancer drugs. Austin, TX: R.G. Landes, 1996.

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The SV40 replicon model for analysis of anticancer drugs. [San Diego, Calif.]: Academic Press, 1996.

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The resonant recognition model of macromolecular bioactivity: Theory and applications. Basel: Birkhäuser Verlag, 1997.

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Sŏ, Yŏng-nok. Yujŏn toksŏng chipʻyo yujŏnja rŭl iyong han yujŏn toksŏng pʻyŏngka model surip yŏnʼgu =: Study on the establishment of evaluation system for genotoxicity using genotoxic biomarker genes. [Seoul]: Sikpʻum Ŭiyakpʻum Anjŏnchʻŏng, 2007.

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Gurgi, Mohamedkamal Ahmed. ESI-MS[n] of anticancer pt[iv] organoamido complexes and their interactions with DNA-model compounds. St. Catharines, Ont: Brock University, Department of Chemistry, 2001.

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Dimitriadi, Konstantina. The use of three pronuclei embryos as a model to analyze the uptake of paternal mitochondrial DNA. Birmingham: University of Birmingham, 1999.

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1959-, Kivshar Y. S., ed. The Frenkel-Kontorova model: Concepts, methods, and applications. Berlin: Springer, 2003.

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Zoya, Ignatova, Martinez-Perez Israel Marck, and SpringerLink (Online service), eds. DNA Computing Models. Boston, MA: Springer-Verlag US, 2008.

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Book chapters on the topic "DNA model"

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Nelson, David O., and Terence P. Speed. "Recovering DNA Sequences from Electrophoresis Data." In Image Models (and their Speech Model Cousins), 141–52. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-4056-3_8.

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Ouldridge, Thomas E. "A Novel DNA Model." In Coarse-Grained Modelling of DNA and DNA Self-Assembly, 21–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30517-7_2.

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Pérez-Jiménez, Mario J., and Fernando Sancho-Caparrini. "Solving Knapsack Problems in a Sticker Based Model." In DNA Computing, 161–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-48017-x_15.

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Khodor, Julia, and David K. Gifford. "Programmed Mutagenesis Is a Universal Model of Computation." In DNA Computing, 300–307. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-48017-x_28.

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Shiozaki, Masashi, Hirotaka Ono, Kunihiko Sadakane, and Masafumi Yamashita. "A Probabilistic Model of the DNA Conformational Change." In DNA Computing, 274–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11925903_21.

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Sahu, Sudheer, Peng Yin, and John H. Reif. "A Self-assembly Model of Time-Dependent Glue Strength." In DNA Computing, 290–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11753681_23.

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Ouldridge, Thomas E. "Thermodynamic Properties of Model DNA." In Coarse-Grained Modelling of DNA and DNA Self-Assembly, 71–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30517-7_6.

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Harvey, Stephen C., and Robert K. Z. Tan. "Development of a Model for DNA Supercoiling." In Unusual DNA Structures, 91–101. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4612-3800-3_6.

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Baskonus, Haci Mehmet, and Carlo Cattani. "Nonlinear Dynamical Model for DNA." In Trends in Mathematics, 115–41. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-3013-1_7.

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Sakakibara, Yasubumi, and Hiroshi Imai. "A DNA-based Computational Model Using a Specific Type of Restriction Enzyme." In DNA Computing, 315–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36440-4_28.

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Conference papers on the topic "DNA model"

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Nishioka, Yuki, Kentaro Doi, and Satoyuki Kawano. "Development of an Electron Scattering Model to Detect Differences in DNA Base Molecules." In ASME-JSME-KSME 2011 Joint Fluids Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajk2011-36031.

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In recent, novel technologies which apply bio-macromolecules to bio-nanodevices attract much attention. Particularly, DNAs have several desirable characteristics: complementary base pairs, self assembly, and electric conductivity. It is expected that high-speed DNA sequencers can be developed by using these specific characteristics of DNAs. In the present study, we develop a theoretical model to analyze the difference of DNA base molecules, in which electron scattering is simulated based on classical electrodynamics and scattering angles are evaluated. Consequently, it is found that scattering
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Erlander, Stig R. "DNA STRUCTURE: EXPERIMENTAL EVIDENCE AGAINST THE WATSON-CRICK DNA MODEL AND FOR THE ERLANDER DNA MODEL." In XXIst International Carbohydrate Symposium 2002. TheScientificWorld Ltd, 2002. http://dx.doi.org/10.1100/tsw.2002.719.

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Boyda, Denis Leonidovich. "Mathematical model of DNA lesions." In XXI International Baldin Seminar on High Energy Physics Problems. Trieste, Italy: Sissa Medialab, 2013. http://dx.doi.org/10.22323/1.173.0042.

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Sajfert, V., Lj Mašković, and D. Popov. "Model explanation of DNA Transcription." In SIXTH INTERNATIONAL CONFERENCE OF THE BALKAN PHYSICAL UNION. AIP, 2007. http://dx.doi.org/10.1063/1.2733564.

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Lillian, Todd D., N. C. Perkins, and S. Goyal. "Computational Elastic Rod Model Applied to DNA Looping." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34956.

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DNA is a long flexible biopolymer containing genetic information. Proteins often take advantage of DNA’s inherent flexibility to perform their cellular functions. Here we present selected results from our computational studies of the mechanical looping of DNA by the Lactose repressor protein. The Lactose repressor resides in the bacterium E. coli and deforms DNA into a loop as a means of controlling the production of enzymes necessary for digesting lactose. We examine this looping process using a computational rod model [1–3] to understand the strain energy and geometry for the resultant DNA l
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Hirsh, Andrew D., Todd D. Lillian, and N. C. Perkins. "A Model for Highly Strained DNA in a Cavity." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48711.

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A single DNA molecule is a long and flexible biopolymer that contains the genetic code. Building upon the discovery of the iconic double helix over 50 years ago, subsequent studies have emphasized how its biological function is related to the mechanical properties of the molecule. A remarkable system which high-lights the role of DNA bending and twisting is the packing and ejection of DNA into and from viral capsids. A recent 3D reconstruction of bacteriophage φ29 reveals a novel toroidal structure thought to be 30–40 bp of highly bent/twisted DNA contained in a small cavity below the capsid.
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Martin, Dan, Mohamad Eid, and Abdulmotaleb El Saddik. "A Haptic Enabled DNA Model Sensing." In 2008 9th International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN '08). IEEE, 2008. http://dx.doi.org/10.1109/i-span.2008.47.

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Liu, Wei, Shouxia Sun, and Ying Guo. "A DNA Computing Model of Perceptron." In 2009 Pacific-Asia Conference on Circuits, Communications and Systems (PACCS). IEEE, 2009. http://dx.doi.org/10.1109/paccs.2009.182.

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Liu, Yaling, and Samir M. Iqbal. "A Mesoscale Model for Molecular Interaction in Functionalized Nanopores." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-68542.

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Nanopores have been used to detect DNA translocation and gene detection. However, the interaction between DNA and nanopore is still not well understood due to the small size of DNA/nanopore and dynamic translocation process. Very recently, various chemical modifications have been applied on nanopore surface for improved signal yield and selective detection. Thus, it is important to characterize the interaction between DNA and chemically modified nanopores. This paper intends to develop an understanding of the interaction between DNA and chemically modified nanopore surface and the translocatio
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Li, Wentian. "DNA segmentation as a model selection process." In the fifth annual international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/369133.369202.

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Reports on the topic "DNA model"

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Jackson, Peter K. DNA Replication Initiator Proteins and Genetic Instability: Creating a Mouse Model for Prostate Cancer. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada392190.

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Mincheff, Milcho S. Naked DNA Immunization for Prevention of Prostate Cancer in a Dunning Rat Prostate Tumor Model. Fort Belvoir, VA: Defense Technical Information Center, June 2003. http://dx.doi.org/10.21236/ada417656.

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Kinney, Shannon R. Examination of the Role of DNA Methylation Changes in Prostate Cancer using the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) Model. Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada502739.

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Morey Kinney, Shannon R. Examination of the Role of DNA Methylation Changes in Prostate Cancer using the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) Model. Fort Belvoir, VA: Defense Technical Information Center, March 2010. http://dx.doi.org/10.21236/ada525616.

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Morey, Shannon R. Examination of the Role of DNA Methylation Changes in Prostate Cancer Using the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) Model. Fort Belvoir, VA: Defense Technical Information Center, March 2008. http://dx.doi.org/10.21236/ada483443.

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Christman, Judith K. Role of DNA Methylation in Altering Gene Expression During the Early Stages of Human Breast Cancer Progression in the MCF10AT Xenograft Model. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada418564.

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Christman, Judith K. Role of DNA Methylation in Altering Gene Expression During the Early Stages of Human Breast Cancer Progression in the MCF10AT Xenograft Model. Fort Belvoir, VA: Defense Technical Information Center, April 2004. http://dx.doi.org/10.21236/ada426221.

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Macedo, Luciana, and Linda Malkas. The Human Breast Cancer DNA Synthesome Can Serve as a Novel In Vitro Model System for Studying the Mechanism of Action of Anticancer Drugs. Fort Belvoir, VA: Defense Technical Information Center, July 2000. http://dx.doi.org/10.21236/ada393926.

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Cucinotta, Francis A. Systems Biology Model of Interactions between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFβ and ATM Signaling. Office of Scientific and Technical Information (OSTI), вересень 2016. http://dx.doi.org/10.2172/1335567.

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O'Neill, Peter, and Jennifer Anderson. Systems Biology Model of Interactions Between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFbeta and ATM Signaling. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1158919.

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