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You searched for subject:(Structure prediction). Showing records 1 – 30 of 293 total matches.

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Rice University

1. Cheng, Yushao. Template-based Protein Structure Prediction and its Applications.

Degree: PhD, Engineering, 2013, Rice University

 Protein structure prediction, also called protein folding, is one of the most significant and challenging research areas in computational biophysics and structural bioinformatics. With the… (more)

Subjects/Keywords: Protein structure prediction

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APA (6th Edition):

Cheng, Y. (2013). Template-based Protein Structure Prediction and its Applications. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/76475

Chicago Manual of Style (16th Edition):

Cheng, Yushao. “Template-based Protein Structure Prediction and its Applications.” 2013. Doctoral Dissertation, Rice University. Accessed March 04, 2021. http://hdl.handle.net/1911/76475.

MLA Handbook (7th Edition):

Cheng, Yushao. “Template-based Protein Structure Prediction and its Applications.” 2013. Web. 04 Mar 2021.

Vancouver:

Cheng Y. Template-based Protein Structure Prediction and its Applications. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1911/76475.

Council of Science Editors:

Cheng Y. Template-based Protein Structure Prediction and its Applications. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/76475


Vanderbilt University

2. Karakaş, Mert. BCL::Fold - de novo protein structure prediction by assembly of secondary structure elements.

Degree: PhD, Chemical and Physical Biology, 2011, Vanderbilt University

 Structural information facilitates understanding of protein function and activity. The limitations of experimental methods for protein structure elucidation in applicability to certain types and families… (more)

Subjects/Keywords: protein structure prediction; contact prediction; de novo

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APA (6th Edition):

Karakaş, M. (2011). BCL::Fold - de novo protein structure prediction by assembly of secondary structure elements. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14981

Chicago Manual of Style (16th Edition):

Karakaş, Mert. “BCL::Fold - de novo protein structure prediction by assembly of secondary structure elements.” 2011. Doctoral Dissertation, Vanderbilt University. Accessed March 04, 2021. http://hdl.handle.net/1803/14981.

MLA Handbook (7th Edition):

Karakaş, Mert. “BCL::Fold - de novo protein structure prediction by assembly of secondary structure elements.” 2011. Web. 04 Mar 2021.

Vancouver:

Karakaş M. BCL::Fold - de novo protein structure prediction by assembly of secondary structure elements. [Internet] [Doctoral dissertation]. Vanderbilt University; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1803/14981.

Council of Science Editors:

Karakaş M. BCL::Fold - de novo protein structure prediction by assembly of secondary structure elements. [Doctoral Dissertation]. Vanderbilt University; 2011. Available from: http://hdl.handle.net/1803/14981


University of Rochester

3. Seetin, Matthew G. RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction.

Degree: PhD, 2011, University of Rochester

 RNAs can function without being translated into proteins. These RNAs adopt a structure or structures to perform these functions, and accurate prediction of structure is… (more)

Subjects/Keywords: RNA Structure; Secondary Structure Prediction; Tertiary Structure Prediction; Pseudoknots

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APA (6th Edition):

Seetin, M. G. (2011). RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/17694

Chicago Manual of Style (16th Edition):

Seetin, Matthew G. “RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction.” 2011. Doctoral Dissertation, University of Rochester. Accessed March 04, 2021. http://hdl.handle.net/1802/17694.

MLA Handbook (7th Edition):

Seetin, Matthew G. “RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction.” 2011. Web. 04 Mar 2021.

Vancouver:

Seetin MG. RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction. [Internet] [Doctoral dissertation]. University of Rochester; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1802/17694.

Council of Science Editors:

Seetin MG. RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction. [Doctoral Dissertation]. University of Rochester; 2011. Available from: http://hdl.handle.net/1802/17694


NSYSU

4. Chen, Chun-jen. A New Fitness Function for Evaluating the Quality of Predicted Protein Structures.

Degree: Master, Computer Science and Engineering, 2010, NSYSU

 For understanding the function of a protein, the protein structure plays an important role. The prediction of protein structure from its primary sequence has significant… (more)

Subjects/Keywords: prediction; tertiary structure; protein

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APA (6th Edition):

Chen, C. (2010). A New Fitness Function for Evaluating the Quality of Predicted Protein Structures. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0902110-103900

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chen, Chun-jen. “A New Fitness Function for Evaluating the Quality of Predicted Protein Structures.” 2010. Thesis, NSYSU. Accessed March 04, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0902110-103900.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chen, Chun-jen. “A New Fitness Function for Evaluating the Quality of Predicted Protein Structures.” 2010. Web. 04 Mar 2021.

Vancouver:

Chen C. A New Fitness Function for Evaluating the Quality of Predicted Protein Structures. [Internet] [Thesis]. NSYSU; 2010. [cited 2021 Mar 04]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0902110-103900.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen C. A New Fitness Function for Evaluating the Quality of Predicted Protein Structures. [Thesis]. NSYSU; 2010. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0902110-103900

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rice University

5. Zang, Tianwu. Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models.

Degree: PhD, Natural Sciences, 2016, Rice University

 Predicting the 3-dimentional structure of protein has been a major interest in the modern computational biology. While lots of successful methods can generate models with… (more)

Subjects/Keywords: Protein Structure Prediction Enhanced Sampling Molecular DynamicsProtein Structure Prediction Enhanced Sampling Molecular DynamicsProtein Structure Prediction Enhanced Sampling Molecular DynamicsProtein Structure Prediction Enhanced Sampling Molecular DynamicsProtein Structure Prediction Enhanced Sampling Molecular DynamicsProtein Structure Prediction Enhanced Sampling Molecular DynamicsProtein Structure Prediction Enhanced Sampling Molecular Dynamics

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APA (6th Edition):

Zang, T. (2016). Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/95649

Chicago Manual of Style (16th Edition):

Zang, Tianwu. “Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models.” 2016. Doctoral Dissertation, Rice University. Accessed March 04, 2021. http://hdl.handle.net/1911/95649.

MLA Handbook (7th Edition):

Zang, Tianwu. “Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models.” 2016. Web. 04 Mar 2021.

Vancouver:

Zang T. Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models. [Internet] [Doctoral dissertation]. Rice University; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1911/95649.

Council of Science Editors:

Zang T. Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models. [Doctoral Dissertation]. Rice University; 2016. Available from: http://hdl.handle.net/1911/95649


University of Georgia

6. Li, Qi. Graph tree decomposition enabled biopolymer folding.

Degree: 2014, University of Georgia

 Biopolymer tertiary structure prediction by computer programs plays a very important role in complementing the experimental determination method. There are two structure prediction approaches: template-based… (more)

Subjects/Keywords: template-based structure prediction; ab initio structure prediction; biopolymer sequence-structure prediction; graph tree decomposition; treewidth; dynamic programming

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APA (6th Edition):

Li, Q. (2014). Graph tree decomposition enabled biopolymer folding. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/26948

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Qi. “Graph tree decomposition enabled biopolymer folding.” 2014. Thesis, University of Georgia. Accessed March 04, 2021. http://hdl.handle.net/10724/26948.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Qi. “Graph tree decomposition enabled biopolymer folding.” 2014. Web. 04 Mar 2021.

Vancouver:

Li Q. Graph tree decomposition enabled biopolymer folding. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10724/26948.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li Q. Graph tree decomposition enabled biopolymer folding. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/26948

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

7. Brunette, TJ. Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction.

Degree: PhD, Computer Science, 2011, U of Massachusetts : PhD

  The most significant impediment for protein structure prediction is the inadequacy of conformation space search. Conformation space is too large and the energy landscape… (more)

Subjects/Keywords: Optimization; Protein Structure Prediction; Search; Computer Sciences

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APA (6th Edition):

Brunette, T. (2011). Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/375

Chicago Manual of Style (16th Edition):

Brunette, TJ. “Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction.” 2011. Doctoral Dissertation, U of Massachusetts : PhD. Accessed March 04, 2021. https://scholarworks.umass.edu/open_access_dissertations/375.

MLA Handbook (7th Edition):

Brunette, TJ. “Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction.” 2011. Web. 04 Mar 2021.

Vancouver:

Brunette T. Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2011. [cited 2021 Mar 04]. Available from: https://scholarworks.umass.edu/open_access_dissertations/375.

Council of Science Editors:

Brunette T. Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction. [Doctoral Dissertation]. U of Massachusetts : PhD; 2011. Available from: https://scholarworks.umass.edu/open_access_dissertations/375

8. Weitzner, Brian D. Next-generation antibody modeling.

Degree: 2015, Johns Hopkins University

 Antibodies are important immunological molecules that can bind a diverse array of foreign molecules. The genetic mechanism that gives rise to antibodies and many antibody… (more)

Subjects/Keywords: Rosetta; antibodies; CDR H3; structure prediction

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APA (6th Edition):

Weitzner, B. D. (2015). Next-generation antibody modeling. (Thesis). Johns Hopkins University. Retrieved from http://jhir.library.jhu.edu/handle/1774.2/37835

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Weitzner, Brian D. “Next-generation antibody modeling.” 2015. Thesis, Johns Hopkins University. Accessed March 04, 2021. http://jhir.library.jhu.edu/handle/1774.2/37835.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Weitzner, Brian D. “Next-generation antibody modeling.” 2015. Web. 04 Mar 2021.

Vancouver:

Weitzner BD. Next-generation antibody modeling. [Internet] [Thesis]. Johns Hopkins University; 2015. [cited 2021 Mar 04]. Available from: http://jhir.library.jhu.edu/handle/1774.2/37835.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Weitzner BD. Next-generation antibody modeling. [Thesis]. Johns Hopkins University; 2015. Available from: http://jhir.library.jhu.edu/handle/1774.2/37835

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Cornell University

9. Tipton, William. Ab-Initio Materials Discovery And Characterization Through Energy Landscape Exploration With An Evolutionary Algorithm.

Degree: PhD, Materials Science and Engineering, 2014, Cornell University

 We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab-initio Hamiltonians. Composition and… (more)

Subjects/Keywords: structure prediction; genetic algorithm; phase diagram

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APA (6th Edition):

Tipton, W. (2014). Ab-Initio Materials Discovery And Characterization Through Energy Landscape Exploration With An Evolutionary Algorithm. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/37141

Chicago Manual of Style (16th Edition):

Tipton, William. “Ab-Initio Materials Discovery And Characterization Through Energy Landscape Exploration With An Evolutionary Algorithm.” 2014. Doctoral Dissertation, Cornell University. Accessed March 04, 2021. http://hdl.handle.net/1813/37141.

MLA Handbook (7th Edition):

Tipton, William. “Ab-Initio Materials Discovery And Characterization Through Energy Landscape Exploration With An Evolutionary Algorithm.” 2014. Web. 04 Mar 2021.

Vancouver:

Tipton W. Ab-Initio Materials Discovery And Characterization Through Energy Landscape Exploration With An Evolutionary Algorithm. [Internet] [Doctoral dissertation]. Cornell University; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1813/37141.

Council of Science Editors:

Tipton W. Ab-Initio Materials Discovery And Characterization Through Energy Landscape Exploration With An Evolutionary Algorithm. [Doctoral Dissertation]. Cornell University; 2014. Available from: http://hdl.handle.net/1813/37141


Vanderbilt University

10. Putnam, Daniel Kent. BCL::SAS- Small Angle X-Ray / Neutron Scattering Profiles to Assist Protein Structure Prediction.

Degree: PhD, Biomedical Informatics, 2016, Vanderbilt University

 The Biochemical Library (BCL) is a protein structure prediction algorithm developed in the Meiler Lab at Vanderbilt University based on the placement of secondary structure(more)

Subjects/Keywords: BCL::Fold; SAXS; Protein Structure Prediction

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APA (6th Edition):

Putnam, D. K. (2016). BCL::SAS- Small Angle X-Ray / Neutron Scattering Profiles to Assist Protein Structure Prediction. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11634

Chicago Manual of Style (16th Edition):

Putnam, Daniel Kent. “BCL::SAS- Small Angle X-Ray / Neutron Scattering Profiles to Assist Protein Structure Prediction.” 2016. Doctoral Dissertation, Vanderbilt University. Accessed March 04, 2021. http://hdl.handle.net/1803/11634.

MLA Handbook (7th Edition):

Putnam, Daniel Kent. “BCL::SAS- Small Angle X-Ray / Neutron Scattering Profiles to Assist Protein Structure Prediction.” 2016. Web. 04 Mar 2021.

Vancouver:

Putnam DK. BCL::SAS- Small Angle X-Ray / Neutron Scattering Profiles to Assist Protein Structure Prediction. [Internet] [Doctoral dissertation]. Vanderbilt University; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1803/11634.

Council of Science Editors:

Putnam DK. BCL::SAS- Small Angle X-Ray / Neutron Scattering Profiles to Assist Protein Structure Prediction. [Doctoral Dissertation]. Vanderbilt University; 2016. Available from: http://hdl.handle.net/1803/11634


University of Cambridge

11. Wynn, Jamie Michael. First-principles structure prediction of extreme nanowires.

Degree: PhD, 2018, University of Cambridge

 Low-dimensional systems are an important and intensely studied area of condensed matter physics. When a material is forced to adopt a low-dimensional structure, its behaviour… (more)

Subjects/Keywords: 620; DFT; Nanowires; Structure prediction; Carbon nanotubes

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APA (6th Edition):

Wynn, J. M. (2018). First-principles structure prediction of extreme nanowires. (Doctoral Dissertation). University of Cambridge. Retrieved from https://doi.org/10.17863/CAM.30362 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763577

Chicago Manual of Style (16th Edition):

Wynn, Jamie Michael. “First-principles structure prediction of extreme nanowires.” 2018. Doctoral Dissertation, University of Cambridge. Accessed March 04, 2021. https://doi.org/10.17863/CAM.30362 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763577.

MLA Handbook (7th Edition):

Wynn, Jamie Michael. “First-principles structure prediction of extreme nanowires.” 2018. Web. 04 Mar 2021.

Vancouver:

Wynn JM. First-principles structure prediction of extreme nanowires. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2021 Mar 04]. Available from: https://doi.org/10.17863/CAM.30362 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763577.

Council of Science Editors:

Wynn JM. First-principles structure prediction of extreme nanowires. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://doi.org/10.17863/CAM.30362 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763577


Vanderbilt University

12. Fischer, Axel Walter. In silico prediction of protein structures and ensembles.

Degree: PhD, Chemistry, 2018, Vanderbilt University

 Determination of a protein’s structural equilibrium constitution remains a challenge. Experimental techniques like X-ray crystallography or nuclear magnetic resonance spectroscopy either are only able to… (more)

Subjects/Keywords: de novo prediction; emre; protein modeling; epr; loop modeling; protein ensemble prediction; protein structure prediction

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APA (6th Edition):

Fischer, A. W. (2018). In silico prediction of protein structures and ensembles. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10422

Chicago Manual of Style (16th Edition):

Fischer, Axel Walter. “In silico prediction of protein structures and ensembles.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed March 04, 2021. http://hdl.handle.net/1803/10422.

MLA Handbook (7th Edition):

Fischer, Axel Walter. “In silico prediction of protein structures and ensembles.” 2018. Web. 04 Mar 2021.

Vancouver:

Fischer AW. In silico prediction of protein structures and ensembles. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1803/10422.

Council of Science Editors:

Fischer AW. In silico prediction of protein structures and ensembles. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://hdl.handle.net/1803/10422

13. Mukherjee, Srayanta. STRUCTURAL MODELING OF PROTEIN-PROTEIN INTERACTIONS USING MULTIPLE-CHAIN THREADING AND FRAGMENT ASSEMBLY.

Degree: PhD, Biochemistry & Molecular Biology, 2011, University of Kansas

 Since its birth, the study of protein structures has made progress with leaps and bounds. However, owing to the expenses and difficulties involved, the number… (more)

Subjects/Keywords: Bioinformatics; Ab intio prediction; Protein-protein interactions; Protein structure prediction; Threading

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APA (6th Edition):

Mukherjee, S. (2011). STRUCTURAL MODELING OF PROTEIN-PROTEIN INTERACTIONS USING MULTIPLE-CHAIN THREADING AND FRAGMENT ASSEMBLY. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/10694

Chicago Manual of Style (16th Edition):

Mukherjee, Srayanta. “STRUCTURAL MODELING OF PROTEIN-PROTEIN INTERACTIONS USING MULTIPLE-CHAIN THREADING AND FRAGMENT ASSEMBLY.” 2011. Doctoral Dissertation, University of Kansas. Accessed March 04, 2021. http://hdl.handle.net/1808/10694.

MLA Handbook (7th Edition):

Mukherjee, Srayanta. “STRUCTURAL MODELING OF PROTEIN-PROTEIN INTERACTIONS USING MULTIPLE-CHAIN THREADING AND FRAGMENT ASSEMBLY.” 2011. Web. 04 Mar 2021.

Vancouver:

Mukherjee S. STRUCTURAL MODELING OF PROTEIN-PROTEIN INTERACTIONS USING MULTIPLE-CHAIN THREADING AND FRAGMENT ASSEMBLY. [Internet] [Doctoral dissertation]. University of Kansas; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1808/10694.

Council of Science Editors:

Mukherjee S. STRUCTURAL MODELING OF PROTEIN-PROTEIN INTERACTIONS USING MULTIPLE-CHAIN THREADING AND FRAGMENT ASSEMBLY. [Doctoral Dissertation]. University of Kansas; 2011. Available from: http://hdl.handle.net/1808/10694


University of Rochester

14. Priore, Salvatore F. (1983 - ). Discovery and characterization of influenza virus RNA secondary structures.

Degree: PhD, 2013, University of Rochester

 PART I: Influenza virus is a significant public health threat, partially because of its capacity to readily exchange gene segments between different host species to… (more)

Subjects/Keywords: GORS; Influenza; RNA; Secondary structure; Structure prediction; Virology

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APA (6th Edition):

Priore, S. F. (. -. ). (2013). Discovery and characterization of influenza virus RNA secondary structures. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/27156

Chicago Manual of Style (16th Edition):

Priore, Salvatore F (1983 - ). “Discovery and characterization of influenza virus RNA secondary structures.” 2013. Doctoral Dissertation, University of Rochester. Accessed March 04, 2021. http://hdl.handle.net/1802/27156.

MLA Handbook (7th Edition):

Priore, Salvatore F (1983 - ). “Discovery and characterization of influenza virus RNA secondary structures.” 2013. Web. 04 Mar 2021.

Vancouver:

Priore SF(-). Discovery and characterization of influenza virus RNA secondary structures. [Internet] [Doctoral dissertation]. University of Rochester; 2013. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1802/27156.

Council of Science Editors:

Priore SF(-). Discovery and characterization of influenza virus RNA secondary structures. [Doctoral Dissertation]. University of Rochester; 2013. Available from: http://hdl.handle.net/1802/27156


University of Rochester

15. Sloma, Michael F. Computational Tools for RNA Structure Prediction.

Degree: PhD, 2018, University of Rochester

 RNA is a versatile biomolecule that functions in many cellular processes. In addition to acting as a template for protein synthesis, RNA plays a direct… (more)

Subjects/Keywords: RNA; Secondary structure; Structure prediction; Bioinformatics; Computational biology; Structural biology.

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APA (6th Edition):

Sloma, M. F. (2018). Computational Tools for RNA Structure Prediction. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/33903

Chicago Manual of Style (16th Edition):

Sloma, Michael F. “Computational Tools for RNA Structure Prediction.” 2018. Doctoral Dissertation, University of Rochester. Accessed March 04, 2021. http://hdl.handle.net/1802/33903.

MLA Handbook (7th Edition):

Sloma, Michael F. “Computational Tools for RNA Structure Prediction.” 2018. Web. 04 Mar 2021.

Vancouver:

Sloma MF. Computational Tools for RNA Structure Prediction. [Internet] [Doctoral dissertation]. University of Rochester; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1802/33903.

Council of Science Editors:

Sloma MF. Computational Tools for RNA Structure Prediction. [Doctoral Dissertation]. University of Rochester; 2018. Available from: http://hdl.handle.net/1802/33903


University of Missouri – Columbia

16. Alazmi, Meshari Saud. Protein structural models selection using 4-mer sequence and combined single and consensus scores.

Degree: 2012, University of Missouri – Columbia

 Quality assessment for protein structure models is an important issue in protein structure prediction. Consensus methods assess each model based on its structural similarity to… (more)

Subjects/Keywords: 4-mer sequence; protein structure prediction; protein structure model

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APA (6th Edition):

Alazmi, M. S. (2012). Protein structural models selection using 4-mer sequence and combined single and consensus scores. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/15238

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Alazmi, Meshari Saud. “Protein structural models selection using 4-mer sequence and combined single and consensus scores.” 2012. Thesis, University of Missouri – Columbia. Accessed March 04, 2021. http://hdl.handle.net/10355/15238.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Alazmi, Meshari Saud. “Protein structural models selection using 4-mer sequence and combined single and consensus scores.” 2012. Web. 04 Mar 2021.

Vancouver:

Alazmi MS. Protein structural models selection using 4-mer sequence and combined single and consensus scores. [Internet] [Thesis]. University of Missouri – Columbia; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10355/15238.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alazmi MS. Protein structural models selection using 4-mer sequence and combined single and consensus scores. [Thesis]. University of Missouri – Columbia; 2012. Available from: http://hdl.handle.net/10355/15238

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Duquesne University

17. Brunetta, Carl David. Structure Determination by X-Ray Diffraction Methods and Physicochemical Characterization of Quaternary Diamond-Like Semiconductors.

Degree: PhD, Chemistry and Biochemistry, 2013, Duquesne University

 Diamond-like semiconductors (DLSs) are a class of semiconductor materials having structures similar to that of either cubic or hexagonal diamond. These normal valence compounds are… (more)

Subjects/Keywords: Chalcogenide; Crystal structure; Diamond-Like; Electronic structure; Prediction; Semiconductor

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Brunetta, C. D. (2013). Structure Determination by X-Ray Diffraction Methods and Physicochemical Characterization of Quaternary Diamond-Like Semiconductors. (Doctoral Dissertation). Duquesne University. Retrieved from https://dsc.duq.edu/etd/359

Chicago Manual of Style (16th Edition):

Brunetta, Carl David. “Structure Determination by X-Ray Diffraction Methods and Physicochemical Characterization of Quaternary Diamond-Like Semiconductors.” 2013. Doctoral Dissertation, Duquesne University. Accessed March 04, 2021. https://dsc.duq.edu/etd/359.

MLA Handbook (7th Edition):

Brunetta, Carl David. “Structure Determination by X-Ray Diffraction Methods and Physicochemical Characterization of Quaternary Diamond-Like Semiconductors.” 2013. Web. 04 Mar 2021.

Vancouver:

Brunetta CD. Structure Determination by X-Ray Diffraction Methods and Physicochemical Characterization of Quaternary Diamond-Like Semiconductors. [Internet] [Doctoral dissertation]. Duquesne University; 2013. [cited 2021 Mar 04]. Available from: https://dsc.duq.edu/etd/359.

Council of Science Editors:

Brunetta CD. Structure Determination by X-Ray Diffraction Methods and Physicochemical Characterization of Quaternary Diamond-Like Semiconductors. [Doctoral Dissertation]. Duquesne University; 2013. Available from: https://dsc.duq.edu/etd/359


University of Missouri – Columbia

18. Eickholt, Jesse. Predicting protein residue-residue contacts and disorder.

Degree: 2013, University of Missouri – Columbia

 [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Predicting a protein's three dimensional structure from its corresponding sequence has long been an extremely… (more)

Subjects/Keywords: protein structure; structure prediction; protein disorder; deep learning

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APA (6th Edition):

Eickholt, J. (2013). Predicting protein residue-residue contacts and disorder. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/37829

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Eickholt, Jesse. “Predicting protein residue-residue contacts and disorder.” 2013. Thesis, University of Missouri – Columbia. Accessed March 04, 2021. https://doi.org/10.32469/10355/37829.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Eickholt, Jesse. “Predicting protein residue-residue contacts and disorder.” 2013. Web. 04 Mar 2021.

Vancouver:

Eickholt J. Predicting protein residue-residue contacts and disorder. [Internet] [Thesis]. University of Missouri – Columbia; 2013. [cited 2021 Mar 04]. Available from: https://doi.org/10.32469/10355/37829.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Eickholt J. Predicting protein residue-residue contacts and disorder. [Thesis]. University of Missouri – Columbia; 2013. Available from: https://doi.org/10.32469/10355/37829

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Vanderbilt University

19. -8010-1279. Doctorate of Philosophy.

Degree: PhD, Chemical & Physical Biology, 2020, Vanderbilt University

 Bioinformatic and epitope mapping approaches have been successful, but are reactive, in determining the mutation preferences and commonly targeted B-cell epitopes of viral fusion proteins.… (more)

Subjects/Keywords: Protein Structure Prediction; multi-state design; contact distance changes; viral fusion; mutation tolerance; epitope prediction

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APA (6th Edition):

-8010-1279. (2020). Doctorate of Philosophy. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10124

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-8010-1279. “Doctorate of Philosophy.” 2020. Doctoral Dissertation, Vanderbilt University. Accessed March 04, 2021. http://hdl.handle.net/1803/10124.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-8010-1279. “Doctorate of Philosophy.” 2020. Web. 04 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-8010-1279. Doctorate of Philosophy. [Internet] [Doctoral dissertation]. Vanderbilt University; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1803/10124.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-8010-1279. Doctorate of Philosophy. [Doctoral Dissertation]. Vanderbilt University; 2020. Available from: http://hdl.handle.net/1803/10124

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


KTH

20. Renhuldt, Nikos Tsardakas. Protein contact prediction based on the Tiramisu deep learning architecture.

Degree: Electrical Engineering and Computer Science (EECS), 2018, KTH

Experimentally determining protein structure is a hard problem, with applications in both medicine and industry. Predicting protein structure is also difficult. Predicted contacts between… (more)

Subjects/Keywords: protein contact prediction; contact prediction; protein structure; deep learning; machine learning; Computer Sciences; Datavetenskap (datalogi)

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APA (6th Edition):

Renhuldt, N. T. (2018). Protein contact prediction based on the Tiramisu deep learning architecture. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231494

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Renhuldt, Nikos Tsardakas. “Protein contact prediction based on the Tiramisu deep learning architecture.” 2018. Thesis, KTH. Accessed March 04, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231494.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Renhuldt, Nikos Tsardakas. “Protein contact prediction based on the Tiramisu deep learning architecture.” 2018. Web. 04 Mar 2021.

Vancouver:

Renhuldt NT. Protein contact prediction based on the Tiramisu deep learning architecture. [Internet] [Thesis]. KTH; 2018. [cited 2021 Mar 04]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231494.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Renhuldt NT. Protein contact prediction based on the Tiramisu deep learning architecture. [Thesis]. KTH; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231494

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

21. Cheng, Rei-Sing. Protein Structure Prediction Based on Secondary Structure Alignment.

Degree: Master, Computer Science and Engineering, 2003, NSYSU

 Sequence alignment is a basic but powerful technique in molecular biology. Macromolecular sequences (DNA, RNA and protein sequences) can be aligned based on some criteria.… (more)

Subjects/Keywords: prediction; structure; alignment; protein; secondary structure

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Cheng, R. (2003). Protein Structure Prediction Based on Secondary Structure Alignment. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821103-204917

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Cheng, Rei-Sing. “Protein Structure Prediction Based on Secondary Structure Alignment.” 2003. Thesis, NSYSU. Accessed March 04, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821103-204917.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Cheng, Rei-Sing. “Protein Structure Prediction Based on Secondary Structure Alignment.” 2003. Web. 04 Mar 2021.

Vancouver:

Cheng R. Protein Structure Prediction Based on Secondary Structure Alignment. [Internet] [Thesis]. NSYSU; 2003. [cited 2021 Mar 04]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821103-204917.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cheng R. Protein Structure Prediction Based on Secondary Structure Alignment. [Thesis]. NSYSU; 2003. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821103-204917

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Vanderbilt University

22. Leman, Julia Koehler. Membrane protein structure determination using NMR spectroscopy and computational techniques.

Degree: PhD, Chemical and Physical Biology, 2012, Vanderbilt University

 Membrane protein structures are very difficult to determine by solution NMR since severe line-broadening obstructs the measurement of restraints. To alleviate this problem we describe… (more)

Subjects/Keywords: paramagnetic NMR restraints; protein structure prediction; protein structure determination; membrane proteins; NMR spectroscopy

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APA (6th Edition):

Leman, J. K. (2012). Membrane protein structure determination using NMR spectroscopy and computational techniques. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/12894

Chicago Manual of Style (16th Edition):

Leman, Julia Koehler. “Membrane protein structure determination using NMR spectroscopy and computational techniques.” 2012. Doctoral Dissertation, Vanderbilt University. Accessed March 04, 2021. http://hdl.handle.net/1803/12894.

MLA Handbook (7th Edition):

Leman, Julia Koehler. “Membrane protein structure determination using NMR spectroscopy and computational techniques.” 2012. Web. 04 Mar 2021.

Vancouver:

Leman JK. Membrane protein structure determination using NMR spectroscopy and computational techniques. [Internet] [Doctoral dissertation]. Vanderbilt University; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1803/12894.

Council of Science Editors:

Leman JK. Membrane protein structure determination using NMR spectroscopy and computational techniques. [Doctoral Dissertation]. Vanderbilt University; 2012. Available from: http://hdl.handle.net/1803/12894


Iowa State University

23. Zimmermann, Michael Thomas. Mechanistic insights on important biomolecules derived using simple dynamics models from extending the reach of elastic network modeling.

Degree: 2011, Iowa State University

 The dynamics of biomolecules are important for carrying out their biologic functions, but these remain difficult to probe in detail experimentally, so that their accurate… (more)

Subjects/Keywords: Elastic Netowrk Modeling; Molecular Function; Molecular Motion; Protein Structure; Structural Biology; Structure Prediction; Bioinformatics

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APA (6th Edition):

Zimmermann, M. T. (2011). Mechanistic insights on important biomolecules derived using simple dynamics models from extending the reach of elastic network modeling. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/12546

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zimmermann, Michael Thomas. “Mechanistic insights on important biomolecules derived using simple dynamics models from extending the reach of elastic network modeling.” 2011. Thesis, Iowa State University. Accessed March 04, 2021. https://lib.dr.iastate.edu/etd/12546.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zimmermann, Michael Thomas. “Mechanistic insights on important biomolecules derived using simple dynamics models from extending the reach of elastic network modeling.” 2011. Web. 04 Mar 2021.

Vancouver:

Zimmermann MT. Mechanistic insights on important biomolecules derived using simple dynamics models from extending the reach of elastic network modeling. [Internet] [Thesis]. Iowa State University; 2011. [cited 2021 Mar 04]. Available from: https://lib.dr.iastate.edu/etd/12546.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zimmermann MT. Mechanistic insights on important biomolecules derived using simple dynamics models from extending the reach of elastic network modeling. [Thesis]. Iowa State University; 2011. Available from: https://lib.dr.iastate.edu/etd/12546

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


New Jersey Institute of Technology

24. Wen, Dongrong. Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis.

Degree: PhD, Computer Science, 2012, New Jersey Institute of Technology

  RNA secondary and tertiary structure motifs play important roles in cells. However, very few web servers are available for RNA motif search and prediction.… (more)

Subjects/Keywords: RNA motif; RNA motif search; Secondary structure; Motif prediction; Tertiary structure; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wen, D. (2012). Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/335

Chicago Manual of Style (16th Edition):

Wen, Dongrong. “Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis.” 2012. Doctoral Dissertation, New Jersey Institute of Technology. Accessed March 04, 2021. https://digitalcommons.njit.edu/dissertations/335.

MLA Handbook (7th Edition):

Wen, Dongrong. “Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis.” 2012. Web. 04 Mar 2021.

Vancouver:

Wen D. Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2012. [cited 2021 Mar 04]. Available from: https://digitalcommons.njit.edu/dissertations/335.

Council of Science Editors:

Wen D. Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis. [Doctoral Dissertation]. New Jersey Institute of Technology; 2012. Available from: https://digitalcommons.njit.edu/dissertations/335


University of Georgia

25. Takata, Mika. Analyses for protein tertiary structure prediction.

Degree: 2014, University of Georgia

 Protein fold classification is essential to recognition of protein tertiary structure. It is of particular interest to the structure analyses of proteins of low sequence… (more)

Subjects/Keywords: Protein; Secondary structure; Protein threading; Structure prediction; Sequence; Alpha-helix; Beta-strand; Coil; Interaction; Visualization

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APA (6th Edition):

Takata, M. (2014). Analyses for protein tertiary structure prediction. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/28133

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Takata, Mika. “Analyses for protein tertiary structure prediction.” 2014. Thesis, University of Georgia. Accessed March 04, 2021. http://hdl.handle.net/10724/28133.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Takata, Mika. “Analyses for protein tertiary structure prediction.” 2014. Web. 04 Mar 2021.

Vancouver:

Takata M. Analyses for protein tertiary structure prediction. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10724/28133.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Takata M. Analyses for protein tertiary structure prediction. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/28133

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Kansas

26. Roy, Ambrish. Protein structure prediction and structure-based protein function annotation.

Degree: PhD, Biochemistry & Molecular Biology, 2011, University of Kansas

 Nature tends to modify rather than invent function of protein molecules, and the log of the modifications is encrypted in the gene sequence. Analysis of… (more)

Subjects/Keywords: Bioinformatics; Biophysics; Biochemistry; Local structure comparison; Protein function annotation; Protein-ligand binding; Protein structure prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Roy, A. (2011). Protein structure prediction and structure-based protein function annotation. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/10695

Chicago Manual of Style (16th Edition):

Roy, Ambrish. “Protein structure prediction and structure-based protein function annotation.” 2011. Doctoral Dissertation, University of Kansas. Accessed March 04, 2021. http://hdl.handle.net/1808/10695.

MLA Handbook (7th Edition):

Roy, Ambrish. “Protein structure prediction and structure-based protein function annotation.” 2011. Web. 04 Mar 2021.

Vancouver:

Roy A. Protein structure prediction and structure-based protein function annotation. [Internet] [Doctoral dissertation]. University of Kansas; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1808/10695.

Council of Science Editors:

Roy A. Protein structure prediction and structure-based protein function annotation. [Doctoral Dissertation]. University of Kansas; 2011. Available from: http://hdl.handle.net/1808/10695


NSYSU

27. Liu, Chu-Kai. Prediction for the Domain of RNA with Support Vector Machine.

Degree: Master, Computer Science and Engineering, 2011, NSYSU

 The three-domain system is a biological classification of RNA. In bioinformatics, predicting the domain of RNA is helpful in the research of DNA and protein.… (more)

Subjects/Keywords: secondary structure; SVM; prediction; RNA; three-domain system

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APA (6th Edition):

Liu, C. (2011). Prediction for the Domain of RNA with Support Vector Machine. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0901111-194100

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Liu, Chu-Kai. “Prediction for the Domain of RNA with Support Vector Machine.” 2011. Thesis, NSYSU. Accessed March 04, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0901111-194100.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Liu, Chu-Kai. “Prediction for the Domain of RNA with Support Vector Machine.” 2011. Web. 04 Mar 2021.

Vancouver:

Liu C. Prediction for the Domain of RNA with Support Vector Machine. [Internet] [Thesis]. NSYSU; 2011. [cited 2021 Mar 04]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0901111-194100.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu C. Prediction for the Domain of RNA with Support Vector Machine. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0901111-194100

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Rochester

28. Xu, Zhenjiang. Non-Coding RNA: From Structure Prediction to Discovery in Genomes.

Degree: PhD, 2013, University of Rochester

 RNA plays remarkably diverse roles in organisms, such as maintaining telomeres, regulating gene expression, and catalyzing reactions. With current techniques, it is often slow and… (more)

Subjects/Keywords: RNA; Secondary Structure; Prediction; Non-Coding RNA; Genomes

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APA (6th Edition):

Xu, Z. (2013). Non-Coding RNA: From Structure Prediction to Discovery in Genomes. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/26787

Chicago Manual of Style (16th Edition):

Xu, Zhenjiang. “Non-Coding RNA: From Structure Prediction to Discovery in Genomes.” 2013. Doctoral Dissertation, University of Rochester. Accessed March 04, 2021. http://hdl.handle.net/1802/26787.

MLA Handbook (7th Edition):

Xu, Zhenjiang. “Non-Coding RNA: From Structure Prediction to Discovery in Genomes.” 2013. Web. 04 Mar 2021.

Vancouver:

Xu Z. Non-Coding RNA: From Structure Prediction to Discovery in Genomes. [Internet] [Doctoral dissertation]. University of Rochester; 2013. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1802/26787.

Council of Science Editors:

Xu Z. Non-Coding RNA: From Structure Prediction to Discovery in Genomes. [Doctoral Dissertation]. University of Rochester; 2013. Available from: http://hdl.handle.net/1802/26787


San Jose State University

29. Kicinski, Maciej. AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS.

Degree: MS, Computer Science, 2011, San Jose State University

  Genes that encode novel proteins are constantly being discovered and added to databases, but the speed with which their structures are being determined is… (more)

Subjects/Keywords: protein structure prediction hidden markov model; Bioinformatics; Other Computer Sciences

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APA (6th Edition):

Kicinski, M. (2011). AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165

Chicago Manual of Style (16th Edition):

Kicinski, Maciej. “AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS.” 2011. Masters Thesis, San Jose State University. Accessed March 04, 2021. https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165.

MLA Handbook (7th Edition):

Kicinski, Maciej. “AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS.” 2011. Web. 04 Mar 2021.

Vancouver:

Kicinski M. AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS. [Internet] [Masters thesis]. San Jose State University; 2011. [cited 2021 Mar 04]. Available from: https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165.

Council of Science Editors:

Kicinski M. AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS. [Masters Thesis]. San Jose State University; 2011. Available from: https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165


San Jose State University

30. Mali, Meenakshee. RNA SECONDARY STRUCTURE PREDICTION TOOL.

Degree: MS, Computer Science, 2011, San Jose State University

  Ribonucleic Acid (RNA) is one of the major macromolecules essential to all forms of life. Apart from the important role played in protein synthesis,… (more)

Subjects/Keywords: RNA Secondary Structure Prediction; Bioinformatics; Other Computer Sciences

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APA (6th Edition):

Mali, M. (2011). RNA SECONDARY STRUCTURE PREDICTION TOOL. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.v9y6-uzac ; https://scholarworks.sjsu.edu/etd_projects/164

Chicago Manual of Style (16th Edition):

Mali, Meenakshee. “RNA SECONDARY STRUCTURE PREDICTION TOOL.” 2011. Masters Thesis, San Jose State University. Accessed March 04, 2021. https://doi.org/10.31979/etd.v9y6-uzac ; https://scholarworks.sjsu.edu/etd_projects/164.

MLA Handbook (7th Edition):

Mali, Meenakshee. “RNA SECONDARY STRUCTURE PREDICTION TOOL.” 2011. Web. 04 Mar 2021.

Vancouver:

Mali M. RNA SECONDARY STRUCTURE PREDICTION TOOL. [Internet] [Masters thesis]. San Jose State University; 2011. [cited 2021 Mar 04]. Available from: https://doi.org/10.31979/etd.v9y6-uzac ; https://scholarworks.sjsu.edu/etd_projects/164.

Council of Science Editors:

Mali M. RNA SECONDARY STRUCTURE PREDICTION TOOL. [Masters Thesis]. San Jose State University; 2011. Available from: https://doi.org/10.31979/etd.v9y6-uzac ; https://scholarworks.sjsu.edu/etd_projects/164

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