Relevant bibliographies by topics / Computational Molecular Biology

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

Academic literature on the topic 'Computational Molecular Biology'

Author: Grafiati
Published: 11 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Computational Molecular Biology"

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Wong, Wing Hung. "Computational Molecular Biology." Journal of the American Statistical Association 95, no. 449 (2000): 322–26. http://dx.doi.org/10.1080/01621459.2000.10473934.

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Sadiku, Matthew N. O., Yonghui Wang, Suxia Cui, and Sarhan M. Musa. "COMPUTATIONAL BIOLOGY." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 6 (2018): 66. http://dx.doi.org/10.23956/ijarcsse.v8i6.616.

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Computation is an integral part of a larger revolution that will affect how science is conducted. Computational biology is an important emerging field of biology which is uniquely enabled by computation. It involves using computers to model biological problems and interpret data, especially problems in evolutionary and molecular biology. The application of computational tools to all areas of biology is producing excitements and insights into biological problems too complex for conventional approaches. This paper provides a brief introduction on computational biology.
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Lloyd, A. "Computational Methods in Molecular Biology." Briefings in Bioinformatics 1, no. 3 (2000): 315–16. http://dx.doi.org/10.1093/bib/1.3.315.

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Martin, D. "Computational Molecular Biology: An Introduction." Briefings in Bioinformatics 2, no. 2 (2001): 204–6. http://dx.doi.org/10.1093/bib/2.2.204.

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Brutlag, Douglas L. "Genomics and computational molecular biology." Current Opinion in Microbiology 1, no. 3 (1998): 340–45. http://dx.doi.org/10.1016/s1369-5274(98)80039-8.

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Hunter, Lawrence. "Progress in computational molecular biology." ACM SIGBIO Newsletter 19, no. 3 (1999): 9–12. http://dx.doi.org/10.1145/340358.340374.

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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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Cai, Yudong, Julio Vera González, Zengrong Liu, and Tao Huang. "Computational Systems Biology Methods in Molecular Biology, Chemistry Biology, Molecular Biomedicine, and Biopharmacy." BioMed Research International 2014 (2014): 1–2. http://dx.doi.org/10.1155/2014/746814.

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Ray, L. B., L. D. Chong, and N. R. Gough. "Computational Biology." Science Signaling 2002, no. 148 (2002): eg10-eg10. http://dx.doi.org/10.1126/stke.2002.148.eg10.

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Casadio, Rita, Boris Lenhard, and Michael J. E. Sternberg. "Computational Resources for Molecular Biology 2021." Journal of Molecular Biology 433, no. 11 (2021): 166962. http://dx.doi.org/10.1016/j.jmb.2021.166962.

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Dissertations / Theses on the topic "Computational Molecular Biology"

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Istrail, Sorin. "Computational molecular biology /." Amsterdam [u.a.] : Elsevier, 2003. http://www.loc.gov/catdir/toc/fy037/2003051360.html.

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Vialette, Stéphane. "Algorithmic Contributions to Computational Molecular Biology." Habilitation à diriger des recherches, Université Paris-Est, 2010. http://tel.archives-ouvertes.fr/tel-00862069.

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Pettersson, Fredrik. "A multivariate approach to computational molecular biology." Doctoral thesis, Umeå : Univ, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-609.

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Dinescu, Adriana. "Metals in Chemistry and Biology: Computational Chemistry Studies." Thesis, University of North Texas, 2007. https://digital.library.unt.edu/ark:/67531/metadc3678/.

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Numerous enzymatic reactions are controlled by the chemistry of metallic ions. This dissertation investigates the electronic properties of three transition metal (copper, chromium, and nickel) complexes and describes modeling studies performed on glutathione synthetase. (1) Copper nitrene complexes were computationally characterized, as these complexes have yet to be experimentally isolated. (2) Multireference calculations were carried out on a symmetric C2v chromium dimer derived from the crystal structure of the [(tBu3SiO)Cr(µ-OSitBu3)]2 complex. (3) The T-shaped geometry of a three-coordina
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Karathia, Hiren Mahendrabhai. "Development and application of computational methdologies for Integrated Molecular Systems Biology." Doctoral thesis, Universitat de Lleida, 2012. http://hdl.handle.net/10803/110518.

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L'objectiu del treball presentat en aquesta tesi va ser el desenvolupament i l'aplicació de metodologies computacionals que integren l’anàlisis de informació sobre seqüències proteiques, informació funcional i genòmica per a la reconstrucció, anotació i organització de proteomes complets, de manera que els resultats es poden comparar entre qualsevol nombre d'organismes amb genomes completament seqüenciats. Metodològicament, m'he centrat en la identificació de l'organització molecular dins d'un proteoma complet d'un organisme de referència i comparació amb proteomes d'altres organismes, en esp
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Donaldson, Eric F. Baric Ralph S. "Computational and molecular biology approaches to viral replication and pathogenesis." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1731.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Sep. 16, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Microbiology and Immunology Virology." Discipline: Microbiology and Immunology; Department/School: Medicine.
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Cao, Dan. "Computational and experimental analysis of mRNA degradationin Saccharomyces cerevisiae." Diss., The University of Arizona, 2002. http://hdl.handle.net/10150/280160.

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Because of its integration power, quantifying power, explanatory power and predictive power, mathematical and computational modeling is becoming an important tool to test and advance our understanding about cellular process in the post-genomic era. Iterative approach between modeling, making prediction and experimental testing might increase the rate of forming and testing hypotheses in Biology. mRNA decay is an ideal system to start knowledge based modeling. In the second chapter, I applied the computational modeling approach to test our understanding about normal mRNA turnover processes in y
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Weis, Michael Christian. "Computational Models of the Mammalian Cell Cycle." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1323278159.

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Ensterö, Mats. "The multi-faceted RNA molecule : Characterization and Function in the regulation of Gene Expression." Doctoral thesis, Stockholm University, Department of Molecular Biology and Functional Genomics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7729.

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<p>In this thesis I have studied the RNA molecule and its function and characteristics in the regulation of gene expression. I have focused on two events that are important for the regulation of the transcriptome: Translational regulation through micro RNAs; and RNA editing through adenosine deaminations.</p><p>Micro RNAs (miRNAs) are ~22 nucleotides long RNA molecules that by semi complementarity bind to untranslated regions of a target messenger RNA (mRNA). The interaction manifests through an RNA/protein complex and act mainly by repressing translation of the target mRNA. I have shown that
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Zwolak, Jason Walter. "Computational Tools for Molecular Networks in Biological Systems." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/30274.

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Theoretical molecular biologists try to understand the workings of cells through mathematics. Some theoreticians use systems of ordinary differential equations (ODEs) as the basis for mathematical modelling of molecular networks. This thesis develops algorithms for estimating molecular reaction rate constants within those mathematical models by fitting the models to experimental data. An additional step is taken to fit non-timecourse experimental data (e.g., transformations must be performed on the ODE solutions before the experimental and simulation data are similar, and therefore, compara
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Books on the topic "Computational Molecular Biology"

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1949-, Leszczynski Jerzy, ed. Computational molecular biology. Elsevier, 1999.

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1960-, Salzberg Steven L., Searls David B, and Kasif Simon, eds. Computational methods in molecular biology. Elsevier, 1998.

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Srinivas, Aluru, ed. Handbook of computational molecular biology. Chapman & Hall/CRC, 2005.

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Pe'er, Itsik, ed. Research in Computational Molecular Biology. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04749-7.

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Singh, Mona, ed. Research in Computational Molecular Biology. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31957-5.

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Chor, Benny, ed. Research in Computational Molecular Biology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29627-7.

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Batzoglou, Serafim, ed. Research in Computational Molecular Biology. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02008-7.

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Berger, Bonnie, ed. Research in Computational Molecular Biology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12683-3.

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Speed, Terry, and Haiyan Huang, eds. Research in Computational Molecular Biology. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71681-5.

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Przytycka, Teresa M., ed. Research in Computational Molecular Biology. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16706-0.

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Book chapters on the topic "Computational Molecular Biology"

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Boukerche, Azzedine, and Alba Cristina Magalhães Alves de Melo. "Computational Molecular Biology." In Parallel Computing for Bioinformatics and Computational Biology. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471756504.ch6.

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Erciyes, K. "Introduction to Molecular Biology." In Computational Biology. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24966-7_2.

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Waterman, Michael S. "Some Molecular Biology." In Introduction to Computational Biology. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-6846-3_2.

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Sharma, Vinamrata, Saumya Tyagi, and Tiratha Raj Singh. "Computational Molecular Evolution." In Bioinformatics and Computational Biology. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003331247-26.

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Kamberaj, Hiqmet. "Computational Molecular Modelling." In Computer Simulations in Molecular Biology. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34839-6_6.

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Oprea, Tudor I., Elebeoba E. May, Andrei Leitão, and Alexander Tropsha. "Computational Systems Chemical Biology." In Methods in Molecular Biology. Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-839-3_18.

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Lodola, Alessio, and Adrian J. Mulholland. "Computational Enzymology." In Methods in Molecular Biology. Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-017-5_4.

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Mahon, Annette S. "A Molecular Supertree of the Artiodactyla." In Computational Biology. Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2330-9_20.

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Tiwary, Basant K. "Molecular Evolution." In Bioinformatics and Computational Biology. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4241-8_6.

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Söllner, Johannes. "Computational Peptide Vaccinology." In Methods in Molecular Biology. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-2285-7_13.

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Conference papers on the topic "Computational Molecular Biology"

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Wang, Hao, Mengmeng Fan, Qing Liu, Zeyu Cui, Dakuo He, and Yue Hou. "A Deep Learning Framework with Multimodal Molecular Representation for Molecular Property Prediction." In 2024 12th International Conference on Bioinformatics and Computational Biology (ICBCB). IEEE, 2024. https://doi.org/10.1109/icbcb61507.2024.11012029.

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Multari, Silvia, Rıza Özçelik, Angelica Mazzolari, Marco Salvatore Nobile, and Francesca Grisoni. "Predicting Metabolic Reactions with a Molecular Transformer for Drug Design Optimization." In 2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2024. http://dx.doi.org/10.1109/cibcb58642.2024.10702115.

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Arrua, Oscar E., Andrej Aderhold, Adriano V. Werhli, and Karina Dos Santos Machado. "RFL-Score: Random Forest with Lasso Scoring Function for Protein-Ligand Molecular Docking." In 2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2024. http://dx.doi.org/10.1109/cibcb58642.2024.10702128.

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de Almeida Vasquez, Felipe James, Arthur Scorsolini Fares, and Silvana Giuliatti. "Machine Learning-Enhanced Molecular Dynamics Analysis of Residue Variant Effects on Human ACE2 and Furin Protein Interactions with SARS-CoV-2 Spike." In 2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2024. http://dx.doi.org/10.1109/cibcb58642.2024.10702125.

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Leon-Morales, Felipe, and Christophe Baete. "Interactions between Cathodic Protection and Initial Stages of MIC in Natural Seawater." In CORROSION 2019. NACE International, 2019. https://doi.org/10.5006/c2019-12844.

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Abstract MIC or microbiological induced corrosion is a serious threat in offshore applications such as wind turbine monopile foundations and mooring chains. This type of localized attack may lead to high corrosion rates affecting the S/N curve which determines the safe operation life of the structure. This paper describes results of laboratory tests on the effectiveness of cathodic protection to prevent or minimize microbiologically influenced corrosion under controlled seawater conditions. Electrochemical, molecular biology and surface characterization technologies are used for identification
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Lesk, Arthur M. "COMPUTATIONAL MOLECULAR BIOLOGY." In Data For Discovery. Begellhouse, 2023. http://dx.doi.org/10.1615/1-56700-002-9.410.

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Donald, Bruce R. "Computational and physical modeling challenges in structural molecular biology and proteomics." In the 2005 ACM symposium. ACM Press, 2005. http://dx.doi.org/10.1145/1060244.1060245.

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"“Dynamic molecular portrait” approach in computational structural biology of membrane proteins." In Биоинформатика регуляции и структуры геномов / системная биология. ИЦиГ СО РАН, 2024. http://dx.doi.org/10.18699/bgrs2024-3.1-33.

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Wei, Guopeng, Connor Walsh, Irina Cazan, and Radu Marculescu. "Molecular tweeting." In BCB '15: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine. ACM, 2015. http://dx.doi.org/10.1145/2808719.2808757.

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Khudyakov, Yury, Ion Mandoiu, Pavel Skums, and Alexander Zelikovsky. "Workshop on Computational Advances in Molecular Epidemiology." In BCB '19: 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. ACM, 2019. http://dx.doi.org/10.1145/3307339.3343859.

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Reports on the topic "Computational Molecular Biology"

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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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Taylor, Ronald C. Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/10108317.

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Taylor, R. C. Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/6057182.

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Hawkins, Brian T., and Sonia Grego. A Better, Faster Road From Biological Data to Human Health: A Systems Biology Approach for Engineered Cell Cultures. RTI Press, 2017. http://dx.doi.org/10.3768/rtipress.2017.rb.0015.1706.

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Traditionally, the interactions of drugs and toxicants with human tissue have been investigated in a reductionist way—for example, by focusing on specific molecular targets and using single-cell-type cultures before testing compounds in whole organisms. More recently, “systems biology” approaches attempt to enhance the predictive value of in vitro biological data by adopting a comprehensive description of biological systems and using computational tools that are sophisticated enough to handle the complexity of these systems. However, the utility of computational models resulting from these eff
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Sheinerman, Felix. Report on the research conducted under the funding of the Sloan foundation postdoctoral fellowship in Computational Molecular Biology [Systematic study of protein-protein complexes] Final report. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/810580.

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Agresar, Grenmarie, and Michael A. Savageau. Final Report, December, 1999. Sloan - US Department of Energy joint postdoctoral fellowship in computational molecular biology [Canonical nonlinear methods for modeling and analyzing gene circuits and spatial variations during pattern formation in embryonic development]. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/811376.

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