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You searched for subject:(RNA Structure Prediction). Showing records 1 – 30 of 34 total matches.

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University of Rochester

1. 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 November 19, 2019. 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. 19 Nov 2019.

Vancouver:

Seetin MG. RNA Structure Prediction:Advancing Both Secondary and Tertiary Structure Prediction. [Internet] [Doctoral dissertation]. University of Rochester; 2011. [cited 2019 Nov 19]. 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


University of Western Australia

2. Sperschneider, Jana. A heuristic method for computational RNA pseudoknot prediction.

Degree: PhD, 2012, University of Western Australia

[Truncated abstract] Macromolecules such as DNA, RNA and proteins have the ability to form diverse threedimensional structures which enable functionality and thus, life. For many… (more)

Subjects/Keywords: RNA structure; Pseudoknot prediction; Structural bioinformatics

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APA (6th Edition):

Sperschneider, J. (2012). A heuristic method for computational RNA pseudoknot prediction. (Doctoral Dissertation). University of Western Australia. Retrieved from http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=33484&local_base=GEN01-INS01

Chicago Manual of Style (16th Edition):

Sperschneider, Jana. “A heuristic method for computational RNA pseudoknot prediction.” 2012. Doctoral Dissertation, University of Western Australia. Accessed November 19, 2019. http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=33484&local_base=GEN01-INS01.

MLA Handbook (7th Edition):

Sperschneider, Jana. “A heuristic method for computational RNA pseudoknot prediction.” 2012. Web. 19 Nov 2019.

Vancouver:

Sperschneider J. A heuristic method for computational RNA pseudoknot prediction. [Internet] [Doctoral dissertation]. University of Western Australia; 2012. [cited 2019 Nov 19]. Available from: http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=33484&local_base=GEN01-INS01.

Council of Science Editors:

Sperschneider J. A heuristic method for computational RNA pseudoknot prediction. [Doctoral Dissertation]. University of Western Australia; 2012. Available from: http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=33484&local_base=GEN01-INS01


University of Houston

3. -4637-1830. RNAdemocracy: a Consensus Scoring Approach for Computational Prediction of RNA Secondary Structures.

Degree: Biology and Biochemistry, Department of, University of Houston

 Computational RNA secondary structure prediction is an important tool for the characterization of nucleic acid. If no sequence homologues are available, the prediction of accurate… (more)

Subjects/Keywords: RNA; Structure prediction

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APA (6th Edition):

-4637-1830. (n.d.). RNAdemocracy: a Consensus Scoring Approach for Computational Prediction of RNA Secondary Structures. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/2868

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-4637-1830. “RNAdemocracy: a Consensus Scoring Approach for Computational Prediction of RNA Secondary Structures.” Thesis, University of Houston. Accessed November 19, 2019. http://hdl.handle.net/10657/2868.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-4637-1830. “RNAdemocracy: a Consensus Scoring Approach for Computational Prediction of RNA Secondary Structures.” Web. 19 Nov 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
No year of publication.

Vancouver:

-4637-1830. RNAdemocracy: a Consensus Scoring Approach for Computational Prediction of RNA Secondary Structures. [Internet] [Thesis]. University of Houston; [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10657/2868.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

-4637-1830. RNAdemocracy: a Consensus Scoring Approach for Computational Prediction of RNA Secondary Structures. [Thesis]. University of Houston; Available from: http://hdl.handle.net/10657/2868

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


University of Georgia

4. Xue, Xingran. Accurate RNA 3D modeling with backbone k-tree model.

Degree: PhD, Computer Science, 2015, University of Georgia

 Given the importance of non-coding Ribonucleic acids (RNAs) to cellular regulatory functions, it would be highly desirable to have accurate computational prediction of RNA 3D… (more)

Subjects/Keywords: K-tree; RNA 3D structure prediction; RNA 3D modeling.

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APA (6th Edition):

Xue, X. (2015). Accurate RNA 3D modeling with backbone k-tree model. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/xue_xingran_201512_phd

Chicago Manual of Style (16th Edition):

Xue, Xingran. “Accurate RNA 3D modeling with backbone k-tree model.” 2015. Doctoral Dissertation, University of Georgia. Accessed November 19, 2019. http://purl.galileo.usg.edu/uga_etd/xue_xingran_201512_phd.

MLA Handbook (7th Edition):

Xue, Xingran. “Accurate RNA 3D modeling with backbone k-tree model.” 2015. Web. 19 Nov 2019.

Vancouver:

Xue X. Accurate RNA 3D modeling with backbone k-tree model. [Internet] [Doctoral dissertation]. University of Georgia; 2015. [cited 2019 Nov 19]. Available from: http://purl.galileo.usg.edu/uga_etd/xue_xingran_201512_phd.

Council of Science Editors:

Xue X. Accurate RNA 3D modeling with backbone k-tree model. [Doctoral Dissertation]. University of Georgia; 2015. Available from: http://purl.galileo.usg.edu/uga_etd/xue_xingran_201512_phd


University of Rochester

5. 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 November 19, 2019. http://hdl.handle.net/1802/26787.

MLA Handbook (7th Edition):

Xu, Zhenjiang. “Non-Coding RNA: From Structure Prediction to Discovery in Genomes.” 2013. Web. 19 Nov 2019.

Vancouver:

Xu Z. Non-Coding RNA: From Structure Prediction to Discovery in Genomes. [Internet] [Doctoral dissertation]. University of Rochester; 2013. [cited 2019 Nov 19]. 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


University of Missouri – Columbia

6. Liu, Liang, 1981-. Physics-based predictions of RNA loop stability and structures.

Degree: 2012, University of Missouri – Columbia

 [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] RNA (ribonucleic acid) molecules play a variety of crucial roles in cellular functions at the… (more)

Subjects/Keywords: Structure prediction; Entropy; RNA loop junction; RNA stability

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APA (6th Edition):

Liu, Liang, 1. (2012). Physics-based predictions of RNA loop stability and structures. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/42561

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, Liang, 1981-. “Physics-based predictions of RNA loop stability and structures.” 2012. Thesis, University of Missouri – Columbia. Accessed November 19, 2019. http://hdl.handle.net/10355/42561.

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

MLA Handbook (7th Edition):

Liu, Liang, 1981-. “Physics-based predictions of RNA loop stability and structures.” 2012. Web. 19 Nov 2019.

Vancouver:

Liu, Liang 1. Physics-based predictions of RNA loop stability and structures. [Internet] [Thesis]. University of Missouri – Columbia; 2012. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10355/42561.

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

Council of Science Editors:

Liu, Liang 1. Physics-based predictions of RNA loop stability and structures. [Thesis]. University of Missouri – Columbia; 2012. Available from: http://hdl.handle.net/10355/42561

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


University of Rochester

7. 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 November 19, 2019. 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. 19 Nov 2019.

Vancouver:

Priore SF(-). Discovery and characterization of influenza virus RNA secondary structures. [Internet] [Doctoral dissertation]. University of Rochester; 2013. [cited 2019 Nov 19]. 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

8. 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 November 19, 2019. http://hdl.handle.net/1802/33903.

MLA Handbook (7th Edition):

Sloma, Michael F. “Computational Tools for RNA Structure Prediction.” 2018. Web. 19 Nov 2019.

Vancouver:

Sloma MF. Computational Tools for RNA Structure Prediction. [Internet] [Doctoral dissertation]. University of Rochester; 2018. [cited 2019 Nov 19]. 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


New Jersey Institute of Technology

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

Degree: PhD, Computer Science, 2011, 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 (6th Edition):

Wen, D. (2011). 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.” 2011. Doctoral Dissertation, New Jersey Institute of Technology. Accessed November 19, 2019. 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.” 2011. Web. 19 Nov 2019.

Vancouver:

Wen D. Design and implementation of a cyberinfrastructure for RNA motif search, prediction and analysis. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2011. [cited 2019 Nov 19]. 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; 2011. Available from: https://digitalcommons.njit.edu/dissertations/335


Georgia Tech

10. Rogers, Emily. A novel method for cluster analysis of RNA structural data.

Degree: PhD, Computational Science and Engineering, 2018, Georgia Tech

 Functional RNA is known to contribute to a host of important biological pathways, with new discoveries being made daily. Because function is dependent on structure,… (more)

Subjects/Keywords: Computational biology; Structural biology; RNA folding; Boltzmann sampling; Cluster analysis; RNA secondary structure prediction

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APA (6th Edition):

Rogers, E. (2018). A novel method for cluster analysis of RNA structural data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60232

Chicago Manual of Style (16th Edition):

Rogers, Emily. “A novel method for cluster analysis of RNA structural data.” 2018. Doctoral Dissertation, Georgia Tech. Accessed November 19, 2019. http://hdl.handle.net/1853/60232.

MLA Handbook (7th Edition):

Rogers, Emily. “A novel method for cluster analysis of RNA structural data.” 2018. Web. 19 Nov 2019.

Vancouver:

Rogers E. A novel method for cluster analysis of RNA structural data. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1853/60232.

Council of Science Editors:

Rogers E. A novel method for cluster analysis of RNA structural data. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60232


University of Georgia

11. Samad, Abdul. Finding optimal spanning k-trees in backbone graphs.

Degree: PhD, Computer Science, 2013, University of Georgia

 Many intractable problems on graphs are polynomial time solvable when the graphs have bounded treewidth. An important class of the graphs with bounded treewidth is… (more)

Subjects/Keywords: RNA Structure Prediction; K-tree; Tree Decoposition; Dynamic Programming

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APA (6th Edition):

Samad, A. (2013). Finding optimal spanning k-trees in backbone graphs. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/samad_abdul_201308_phd

Chicago Manual of Style (16th Edition):

Samad, Abdul. “Finding optimal spanning k-trees in backbone graphs.” 2013. Doctoral Dissertation, University of Georgia. Accessed November 19, 2019. http://purl.galileo.usg.edu/uga_etd/samad_abdul_201308_phd.

MLA Handbook (7th Edition):

Samad, Abdul. “Finding optimal spanning k-trees in backbone graphs.” 2013. Web. 19 Nov 2019.

Vancouver:

Samad A. Finding optimal spanning k-trees in backbone graphs. [Internet] [Doctoral dissertation]. University of Georgia; 2013. [cited 2019 Nov 19]. Available from: http://purl.galileo.usg.edu/uga_etd/samad_abdul_201308_phd.

Council of Science Editors:

Samad A. Finding optimal spanning k-trees in backbone graphs. [Doctoral Dissertation]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/samad_abdul_201308_phd

12. Shareghi Arani, Pooya. Graph generating systems for predicting biological structures.

Degree: PhD, Computer Science, 2012, University of Georgia

 Computational predictions of RNA and protein structures have become necessary complements to the expensive experimental methods of structure elucidation. In this dissertation, we present two… (more)

Subjects/Keywords: RNA Structure Prediction

structure prediction. We also discuss how our framework for the RNA tertiary structure prediction… …the same structure means that RNA structure prediction cannot simply be solved using… …66], and offered a viable venue toward RNA tertiary structure prediction [36, 41… …long RNA and identify the coaxial stacking of its helices. RNA secondary structure prediction… …or productions), a set of terminal symbols 15 Figure 2.7: RNA structure prediction… 

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APA (6th Edition):

Shareghi Arani, P. (2012). Graph generating systems for predicting biological structures. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/shareghi-arani_pooya_201205_phd

Chicago Manual of Style (16th Edition):

Shareghi Arani, Pooya. “Graph generating systems for predicting biological structures.” 2012. Doctoral Dissertation, University of Georgia. Accessed November 19, 2019. http://purl.galileo.usg.edu/uga_etd/shareghi-arani_pooya_201205_phd.

MLA Handbook (7th Edition):

Shareghi Arani, Pooya. “Graph generating systems for predicting biological structures.” 2012. Web. 19 Nov 2019.

Vancouver:

Shareghi Arani P. Graph generating systems for predicting biological structures. [Internet] [Doctoral dissertation]. University of Georgia; 2012. [cited 2019 Nov 19]. Available from: http://purl.galileo.usg.edu/uga_etd/shareghi-arani_pooya_201205_phd.

Council of Science Editors:

Shareghi Arani P. Graph generating systems for predicting biological structures. [Doctoral Dissertation]. University of Georgia; 2012. Available from: http://purl.galileo.usg.edu/uga_etd/shareghi-arani_pooya_201205_phd


NSYSU

13. 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 November 19, 2019. 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. 19 Nov 2019.

Vancouver:

Liu C. Prediction for the Domain of RNA with Support Vector Machine. [Internet] [Thesis]. NSYSU; 2011. [cited 2019 Nov 19]. 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


Wayne State University

14. Forouzmand, Elmirasadat. The Rna Newton Polytope And Learnability Of Energy Parameters.

Degree: MS, Computer Science, 2014, Wayne State University

  Computational RNA secondary structure prediction has been a topic of much research interest for several decades now. Despite all the progress made in the… (more)

Subjects/Keywords: Bioinformatics; Newton Polytope; RNA structure prediction; Bioinformatics; Computer Sciences

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APA (6th Edition):

Forouzmand, E. (2014). The Rna Newton Polytope And Learnability Of Energy Parameters. (Masters Thesis). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_theses/329

Chicago Manual of Style (16th Edition):

Forouzmand, Elmirasadat. “The Rna Newton Polytope And Learnability Of Energy Parameters.” 2014. Masters Thesis, Wayne State University. Accessed November 19, 2019. https://digitalcommons.wayne.edu/oa_theses/329.

MLA Handbook (7th Edition):

Forouzmand, Elmirasadat. “The Rna Newton Polytope And Learnability Of Energy Parameters.” 2014. Web. 19 Nov 2019.

Vancouver:

Forouzmand E. The Rna Newton Polytope And Learnability Of Energy Parameters. [Internet] [Masters thesis]. Wayne State University; 2014. [cited 2019 Nov 19]. Available from: https://digitalcommons.wayne.edu/oa_theses/329.

Council of Science Editors:

Forouzmand E. The Rna Newton Polytope And Learnability Of Energy Parameters. [Masters Thesis]. Wayne State University; 2014. Available from: https://digitalcommons.wayne.edu/oa_theses/329


San Jose State University

15. 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 November 19, 2019. 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. 19 Nov 2019.

Vancouver:

Mali M. RNA SECONDARY STRUCTURE PREDICTION TOOL. [Internet] [Masters thesis]. San Jose State University; 2011. [cited 2019 Nov 19]. 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


University of Edinburgh

16. Selega, Alina. Computational methods for RNA integrative biology.

Degree: PhD, 2018, University of Edinburgh

 Ribonucleic acid (RNA) is an essential molecule, which carries out a wide variety of functions within the cell, from its crucial involvement in protein synthesis… (more)

Subjects/Keywords: RNA; next-generation sequencing; NGS; RNA structure probing; automated bias-correcting strategies; structure prediction algorithms; modelling

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APA (6th Edition):

Selega, A. (2018). Computational methods for RNA integrative biology. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/29630

Chicago Manual of Style (16th Edition):

Selega, Alina. “Computational methods for RNA integrative biology.” 2018. Doctoral Dissertation, University of Edinburgh. Accessed November 19, 2019. http://hdl.handle.net/1842/29630.

MLA Handbook (7th Edition):

Selega, Alina. “Computational methods for RNA integrative biology.” 2018. Web. 19 Nov 2019.

Vancouver:

Selega A. Computational methods for RNA integrative biology. [Internet] [Doctoral dissertation]. University of Edinburgh; 2018. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1842/29630.

Council of Science Editors:

Selega A. Computational methods for RNA integrative biology. [Doctoral Dissertation]. University of Edinburgh; 2018. Available from: http://hdl.handle.net/1842/29630


Université Paris-Sud – Paris XI

17. Zeng, Cong. Classification of RNA Pseudoknots and Comparison of Structure Prediction Methods : Classification de Pseudo-nœuds d'ARN et Comparaison de Méthodes de Prédiction de Structure.

Degree: Docteur es, Bioinformatique, 2015, Université Paris-Sud – Paris XI

De nombreuses recherches ont constaté l'importance des molécules d'ARN, car ils jouent un rôle vital dans beaucoup de procédures moléculaires. Et il est accepté généralement… (more)

Subjects/Keywords: ARN; Structure secondaire; Pseudo-noeuds; Classification; Prédiction de structure; Comparaison; Benchmark; RNA; Secondary strucure; Pseudoknot; Classification; Structure prediction; Comparison; Benchmark

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

APA (6th Edition):

Zeng, C. (2015). Classification of RNA Pseudoknots and Comparison of Structure Prediction Methods : Classification de Pseudo-nœuds d'ARN et Comparaison de Méthodes de Prédiction de Structure. (Doctoral Dissertation). Université Paris-Sud – Paris XI. Retrieved from http://www.theses.fr/2015PA112127

Chicago Manual of Style (16th Edition):

Zeng, Cong. “Classification of RNA Pseudoknots and Comparison of Structure Prediction Methods : Classification de Pseudo-nœuds d'ARN et Comparaison de Méthodes de Prédiction de Structure.” 2015. Doctoral Dissertation, Université Paris-Sud – Paris XI. Accessed November 19, 2019. http://www.theses.fr/2015PA112127.

MLA Handbook (7th Edition):

Zeng, Cong. “Classification of RNA Pseudoknots and Comparison of Structure Prediction Methods : Classification de Pseudo-nœuds d'ARN et Comparaison de Méthodes de Prédiction de Structure.” 2015. Web. 19 Nov 2019.

Vancouver:

Zeng C. Classification of RNA Pseudoknots and Comparison of Structure Prediction Methods : Classification de Pseudo-nœuds d'ARN et Comparaison de Méthodes de Prédiction de Structure. [Internet] [Doctoral dissertation]. Université Paris-Sud – Paris XI; 2015. [cited 2019 Nov 19]. Available from: http://www.theses.fr/2015PA112127.

Council of Science Editors:

Zeng C. Classification of RNA Pseudoknots and Comparison of Structure Prediction Methods : Classification de Pseudo-nœuds d'ARN et Comparaison de Méthodes de Prédiction de Structure. [Doctoral Dissertation]. Université Paris-Sud – Paris XI; 2015. Available from: http://www.theses.fr/2015PA112127


University of Illinois – Chicago

18. Tang, Ke. Efficient Biased Sampling Methods for Biomacromolecules: Protein Loops and RNA Thermodynamic Prediction.

Degree: 2016, University of Illinois – Chicago

 Biomacromolecules are fundamental structural and functional units of cell. Nucleic acids and proteins are the most common biomacromolecules. The relationship between sequences and structures of… (more)

Subjects/Keywords: Chain-growth method; Structure Prediction; Conformational Sampling; Protein Loop; RNA pseudoknot; Thermodynamics; Antibody

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APA (6th Edition):

Tang, K. (2016). Efficient Biased Sampling Methods for Biomacromolecules: Protein Loops and RNA Thermodynamic Prediction. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21306

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):

Tang, Ke. “Efficient Biased Sampling Methods for Biomacromolecules: Protein Loops and RNA Thermodynamic Prediction.” 2016. Thesis, University of Illinois – Chicago. Accessed November 19, 2019. http://hdl.handle.net/10027/21306.

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

MLA Handbook (7th Edition):

Tang, Ke. “Efficient Biased Sampling Methods for Biomacromolecules: Protein Loops and RNA Thermodynamic Prediction.” 2016. Web. 19 Nov 2019.

Vancouver:

Tang K. Efficient Biased Sampling Methods for Biomacromolecules: Protein Loops and RNA Thermodynamic Prediction. [Internet] [Thesis]. University of Illinois – Chicago; 2016. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10027/21306.

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

Council of Science Editors:

Tang K. Efficient Biased Sampling Methods for Biomacromolecules: Protein Loops and RNA Thermodynamic Prediction. [Thesis]. University of Illinois – Chicago; 2016. Available from: http://hdl.handle.net/10027/21306

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


Bowling Green State University

19. Roll, James Elwood. Inferring RNA 3D Motifs from Sequence.

Degree: PhD, Statistics, 2019, Bowling Green State University

 An outstanding problem in molecular biology is the prediction of the 3D structure of RNA molecules based on the sequence of the RNA. An important… (more)

Subjects/Keywords: Bioinformatics; Statistics; RNA 3D structure prediction; stochastic context free gramars; markov random fields

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

APA (6th Edition):

Roll, J. E. (2019). Inferring RNA 3D Motifs from Sequence. (Doctoral Dissertation). Bowling Green State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1557482505513958

Chicago Manual of Style (16th Edition):

Roll, James Elwood. “Inferring RNA 3D Motifs from Sequence.” 2019. Doctoral Dissertation, Bowling Green State University. Accessed November 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1557482505513958.

MLA Handbook (7th Edition):

Roll, James Elwood. “Inferring RNA 3D Motifs from Sequence.” 2019. Web. 19 Nov 2019.

Vancouver:

Roll JE. Inferring RNA 3D Motifs from Sequence. [Internet] [Doctoral dissertation]. Bowling Green State University; 2019. [cited 2019 Nov 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1557482505513958.

Council of Science Editors:

Roll JE. Inferring RNA 3D Motifs from Sequence. [Doctoral Dissertation]. Bowling Green State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1557482505513958


University of British Columbia

20. Andronescu, Mirela Stefania. Computational approaches for RNA energy parameter estimation .

Degree: 2008, University of British Columbia

RNA molecules play important roles, including catalysis of chemical reactions and control of gene expression, and their functions largely depend on their folded structures. Since… (more)

Subjects/Keywords: RNA secondary structure prediction; RNA energy models

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

APA (6th Edition):

Andronescu, M. S. (2008). Computational approaches for RNA energy parameter estimation . (Thesis). University of British Columbia. Retrieved from http://hdl.handle.net/2429/2794

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):

Andronescu, Mirela Stefania. “Computational approaches for RNA energy parameter estimation .” 2008. Thesis, University of British Columbia. Accessed November 19, 2019. http://hdl.handle.net/2429/2794.

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

MLA Handbook (7th Edition):

Andronescu, Mirela Stefania. “Computational approaches for RNA energy parameter estimation .” 2008. Web. 19 Nov 2019.

Vancouver:

Andronescu MS. Computational approaches for RNA energy parameter estimation . [Internet] [Thesis]. University of British Columbia; 2008. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/2429/2794.

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

Council of Science Editors:

Andronescu MS. Computational approaches for RNA energy parameter estimation . [Thesis]. University of British Columbia; 2008. Available from: http://hdl.handle.net/2429/2794

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


Iowa State University

21. Cho, Hyejin. Computational prediction, experiment design and statistical validations of non-coding regulatory RNA.

Degree: 2015, Iowa State University

 Non-coding regulatory RNAs (ncRNAs) regulate a host of gene functions in prokaryotes, e.g., transcription and translation regulations, RNA processing and modification, and mRNA stability. Some… (more)

Subjects/Keywords: Bioinformatics and Computational Biology; non-conding regulatory RNA; PICKY; Prediction; RNA secondary structure; Whole genome tiling microarray; Bioinformatics; Computational Biology

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

APA (6th Edition):

Cho, H. (2015). Computational prediction, experiment design and statistical validations of non-coding regulatory RNA. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/14672

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):

Cho, Hyejin. “Computational prediction, experiment design and statistical validations of non-coding regulatory RNA.” 2015. Thesis, Iowa State University. Accessed November 19, 2019. https://lib.dr.iastate.edu/etd/14672.

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

MLA Handbook (7th Edition):

Cho, Hyejin. “Computational prediction, experiment design and statistical validations of non-coding regulatory RNA.” 2015. Web. 19 Nov 2019.

Vancouver:

Cho H. Computational prediction, experiment design and statistical validations of non-coding regulatory RNA. [Internet] [Thesis]. Iowa State University; 2015. [cited 2019 Nov 19]. Available from: https://lib.dr.iastate.edu/etd/14672.

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

Council of Science Editors:

Cho H. Computational prediction, experiment design and statistical validations of non-coding regulatory RNA. [Thesis]. Iowa State University; 2015. Available from: https://lib.dr.iastate.edu/etd/14672

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


University of Gothenburg / Göteborgs Universitet

22. Davila Lopez, Marcela. Evolution of protein and non-coding RNA genes studied with comparative genomics.

Degree: 2010, University of Gothenburg / Göteborgs Universitet

 The identification of protein and non-coding RNA (ncRNA) genes is one important step in the analysis of a genome. This thesis focuses on the identification… (more)

Subjects/Keywords: Bioinformatics; evolution; non-coding RNA; gene prediction; gene order; bidirectional promoter; homologue prediction; secondary structure; RNAse P; RNase MRP

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APA (6th Edition):

Davila Lopez, M. (2010). Evolution of protein and non-coding RNA genes studied with comparative genomics. (Thesis). University of Gothenburg / Göteborgs Universitet. Retrieved from http://hdl.handle.net/2077/23816

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):

Davila Lopez, Marcela. “Evolution of protein and non-coding RNA genes studied with comparative genomics.” 2010. Thesis, University of Gothenburg / Göteborgs Universitet. Accessed November 19, 2019. http://hdl.handle.net/2077/23816.

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

MLA Handbook (7th Edition):

Davila Lopez, Marcela. “Evolution of protein and non-coding RNA genes studied with comparative genomics.” 2010. Web. 19 Nov 2019.

Vancouver:

Davila Lopez M. Evolution of protein and non-coding RNA genes studied with comparative genomics. [Internet] [Thesis]. University of Gothenburg / Göteborgs Universitet; 2010. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/2077/23816.

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

Council of Science Editors:

Davila Lopez M. Evolution of protein and non-coding RNA genes studied with comparative genomics. [Thesis]. University of Gothenburg / Göteborgs Universitet; 2010. Available from: http://hdl.handle.net/2077/23816

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


University of Vienna

23. Beyer, Wolfgang. RNA secondary structure prediction including pseudoknots.

Degree: 2010, University of Vienna

RNAs sind sehr wichtige Biomoleküle. Früher sah man in ihnen nur die Zwischenstufe zwischen DNA, dem Träger der genetischen Information, und Proteinen, den Katalysatoren biochemischer… (more)

Subjects/Keywords: 42.10 Theoretische Biologie; 54.99 Informatik: Sonstiges; 42.13 Molekularbiologie; 42.99 Biologie: Sonstiges; RNA / Sekundärstruktur / Strukturvorhersage / Pseudoknoten / Dynamic Programming / Bioinformatik; RNA / secondary structure / structure prediction / pseudoknot / dynamic programming / bioinformatics

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

APA (6th Edition):

Beyer, W. (2010). RNA secondary structure prediction including pseudoknots. (Thesis). University of Vienna. Retrieved from http://othes.univie.ac.at/11587/

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):

Beyer, Wolfgang. “RNA secondary structure prediction including pseudoknots.” 2010. Thesis, University of Vienna. Accessed November 19, 2019. http://othes.univie.ac.at/11587/.

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

MLA Handbook (7th Edition):

Beyer, Wolfgang. “RNA secondary structure prediction including pseudoknots.” 2010. Web. 19 Nov 2019.

Vancouver:

Beyer W. RNA secondary structure prediction including pseudoknots. [Internet] [Thesis]. University of Vienna; 2010. [cited 2019 Nov 19]. Available from: http://othes.univie.ac.at/11587/.

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

Council of Science Editors:

Beyer W. RNA secondary structure prediction including pseudoknots. [Thesis]. University of Vienna; 2010. Available from: http://othes.univie.ac.at/11587/

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


University of Vienna

24. Beckmann, Irene Katharina. Identification and classification of pseudoknots and their impact on RNA 3D structure prediction.

Degree: 2018, University of Vienna

Die hier präsentierte Arbeit befasst sich mit der Vorhersage der Struktur von noncoding RNA. Im Zuge dessen wird ein kurzer Überblick über die unterschiedlichen Arten… (more)

Subjects/Keywords: 42.13 Molekularbiologie; 35.75 Nukleinsäuren; 35.06 Computeranwendungen; RNS / RNA / Ribonukleinsäure / Pseudoknoten / 3D / tertiär Struktur / Ernwin / Forgi / Struktur Vorhersage; RNA / ribonucleic acid / pseudoknots / 3D / tertiary structure / Ernwin / Forgi / structure prediction

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APA (6th Edition):

Beckmann, I. K. (2018). Identification and classification of pseudoknots and their impact on RNA 3D structure prediction. (Thesis). University of Vienna. Retrieved from http://othes.univie.ac.at/52151/

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):

Beckmann, Irene Katharina. “Identification and classification of pseudoknots and their impact on RNA 3D structure prediction.” 2018. Thesis, University of Vienna. Accessed November 19, 2019. http://othes.univie.ac.at/52151/.

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

MLA Handbook (7th Edition):

Beckmann, Irene Katharina. “Identification and classification of pseudoknots and their impact on RNA 3D structure prediction.” 2018. Web. 19 Nov 2019.

Vancouver:

Beckmann IK. Identification and classification of pseudoknots and their impact on RNA 3D structure prediction. [Internet] [Thesis]. University of Vienna; 2018. [cited 2019 Nov 19]. Available from: http://othes.univie.ac.at/52151/.

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

Council of Science Editors:

Beckmann IK. Identification and classification of pseudoknots and their impact on RNA 3D structure prediction. [Thesis]. University of Vienna; 2018. Available from: http://othes.univie.ac.at/52151/

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


University of Melbourne

25. Ansell, Brendan Robert Edward. Mechanisms of drug response and resistance in Giardia duodenalis.

Degree: 2017, University of Melbourne

 Giardia duodenalis is a parasitic protist and the most common intestinal parasite of humans, causing 200-300 million cases of diarrhoeal disease annually. Metronidazole is a… (more)

Subjects/Keywords: Giardia; Giardia duodenalis; Giardia intestinalis; Giardia lamblia; metronidazole; drug resistance; oxidoreductase; RNA sequencing; protein structure prediction; machine learning; reverse genetics

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APA (6th Edition):

Ansell, B. R. E. (2017). Mechanisms of drug response and resistance in Giardia duodenalis. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/191625

Chicago Manual of Style (16th Edition):

Ansell, Brendan Robert Edward. “Mechanisms of drug response and resistance in Giardia duodenalis.” 2017. Doctoral Dissertation, University of Melbourne. Accessed November 19, 2019. http://hdl.handle.net/11343/191625.

MLA Handbook (7th Edition):

Ansell, Brendan Robert Edward. “Mechanisms of drug response and resistance in Giardia duodenalis.” 2017. Web. 19 Nov 2019.

Vancouver:

Ansell BRE. Mechanisms of drug response and resistance in Giardia duodenalis. [Internet] [Doctoral dissertation]. University of Melbourne; 2017. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/11343/191625.

Council of Science Editors:

Ansell BRE. Mechanisms of drug response and resistance in Giardia duodenalis. [Doctoral Dissertation]. University of Melbourne; 2017. Available from: http://hdl.handle.net/11343/191625


New Jersey Institute of Technology

26. Slotman, Justin. RNA secondary structure detection programs with an emphasis on covariance models.

Degree: MSin Bioinformatics - (M.S.), Computer Science, 2008, New Jersey Institute of Technology

RNA secondary structure prediction requires a different approach from traditional alignment methods. Functional RNAs often have their secondary structure better conserved than their primary… (more)

Subjects/Keywords: RNA secondary structure prediction; Covariance models; Bioinformatics; Computer Sciences

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APA (6th Edition):

Slotman, J. (2008). RNA secondary structure detection programs with an emphasis on covariance models. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/304

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):

Slotman, Justin. “RNA secondary structure detection programs with an emphasis on covariance models.” 2008. Thesis, New Jersey Institute of Technology. Accessed November 19, 2019. https://digitalcommons.njit.edu/theses/304.

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

MLA Handbook (7th Edition):

Slotman, Justin. “RNA secondary structure detection programs with an emphasis on covariance models.” 2008. Web. 19 Nov 2019.

Vancouver:

Slotman J. RNA secondary structure detection programs with an emphasis on covariance models. [Internet] [Thesis]. New Jersey Institute of Technology; 2008. [cited 2019 Nov 19]. Available from: https://digitalcommons.njit.edu/theses/304.

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

Council of Science Editors:

Slotman J. RNA secondary structure detection programs with an emphasis on covariance models. [Thesis]. New Jersey Institute of Technology; 2008. Available from: https://digitalcommons.njit.edu/theses/304

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


Brno University of Technology

27. Klímová, Markéta. Predikce sekundární struktury RNA sekvencí .

Degree: 2015, Brno University of Technology

 Sekundární struktura RNA hraje roli v mnoha biologických procesech. Efektivní predikce této struktury může poskytnout informace pro další zkoumání těchto procesů. V současnosti existuje mnoho… (more)

Subjects/Keywords: RNA; predikce sekundární struktury; mfold; RNAfold; Sfold; Nussinov-Jacobson; Zuker; minimalizace volné energie; RNA; secondary structure prediction; mfold; RNAfold; Sfold; Nussinov-Jacobson; Zuker; free energy minimization

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APA (6th Edition):

Klímová, M. (2015). Predikce sekundární struktury RNA sekvencí . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/38951

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):

Klímová, Markéta. “Predikce sekundární struktury RNA sekvencí .” 2015. Thesis, Brno University of Technology. Accessed November 19, 2019. http://hdl.handle.net/11012/38951.

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

MLA Handbook (7th Edition):

Klímová, Markéta. “Predikce sekundární struktury RNA sekvencí .” 2015. Web. 19 Nov 2019.

Vancouver:

Klímová M. Predikce sekundární struktury RNA sekvencí . [Internet] [Thesis]. Brno University of Technology; 2015. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/11012/38951.

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

Council of Science Editors:

Klímová M. Predikce sekundární struktury RNA sekvencí . [Thesis]. Brno University of Technology; 2015. Available from: http://hdl.handle.net/11012/38951

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


University of Central Florida

28. Li, Yuan. Computational Methods For Analyzing Rna Folding Landscapes And Its Applications.

Degree: 2012, University of Central Florida

 Non-protein-coding RNAs play critical regulatory roles in cellular life. Many ncRNAs fold into specific structures in order to perform their biological functions. Some of the… (more)

Subjects/Keywords: Rna secondary structures; stable local optimal rna structure; consensus folding; riboswitch prediction; Computer Sciences; Engineering; Dissertations, Academic  – Engineering and Computer Science, Engineering and Computer Science  – Dissertations, Academic

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

APA (6th Edition):

Li, Y. (2012). Computational Methods For Analyzing Rna Folding Landscapes And Its Applications. (Doctoral Dissertation). University of Central Florida. Retrieved from https://stars.library.ucf.edu/etd/2475

Chicago Manual of Style (16th Edition):

Li, Yuan. “Computational Methods For Analyzing Rna Folding Landscapes And Its Applications.” 2012. Doctoral Dissertation, University of Central Florida. Accessed November 19, 2019. https://stars.library.ucf.edu/etd/2475.

MLA Handbook (7th Edition):

Li, Yuan. “Computational Methods For Analyzing Rna Folding Landscapes And Its Applications.” 2012. Web. 19 Nov 2019.

Vancouver:

Li Y. Computational Methods For Analyzing Rna Folding Landscapes And Its Applications. [Internet] [Doctoral dissertation]. University of Central Florida; 2012. [cited 2019 Nov 19]. Available from: https://stars.library.ucf.edu/etd/2475.

Council of Science Editors:

Li Y. Computational Methods For Analyzing Rna Folding Landscapes And Its Applications. [Doctoral Dissertation]. University of Central Florida; 2012. Available from: https://stars.library.ucf.edu/etd/2475

29. Pan, Minmin. RNA secondary sturcture prediction using a combined method of thermodynamics and kinetics.

Degree: MS, Biology, 2011, Georgia Tech

 Nowadays, RNA is extensively acknowledged an important role in the functions of information transfer, structural components, gene regulation and etc. The secondary structure of RNA(more)

Subjects/Keywords: MFE; RNA secondary structure prediction; Kinetics; Molecules; Genetic transcription

prediction of RNA secondary structure does not only provide possible structures, but also… …computational methods to solve the RNA secondary structure prediction problem. 1.1 Conventional RNA… …efficient algorithms for RNA secondary structure prediction (20-23) using dynamic… …UNAfold and RNAfold are MFE RNA secondary structure prediction programs, serving here as… …structure of RNA becomes a key to understand structure-function relationship. Computational… 

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APA (6th Edition):

Pan, M. (2011). RNA secondary sturcture prediction using a combined method of thermodynamics and kinetics. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44891

Chicago Manual of Style (16th Edition):

Pan, Minmin. “RNA secondary sturcture prediction using a combined method of thermodynamics and kinetics.” 2011. Masters Thesis, Georgia Tech. Accessed November 19, 2019. http://hdl.handle.net/1853/44891.

MLA Handbook (7th Edition):

Pan, Minmin. “RNA secondary sturcture prediction using a combined method of thermodynamics and kinetics.” 2011. Web. 19 Nov 2019.

Vancouver:

Pan M. RNA secondary sturcture prediction using a combined method of thermodynamics and kinetics. [Internet] [Masters thesis]. Georgia Tech; 2011. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1853/44891.

Council of Science Editors:

Pan M. RNA secondary sturcture prediction using a combined method of thermodynamics and kinetics. [Masters Thesis]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/44891

30. Leonardis, Eleonora De. Méthodes pour l'inférence en grande dimension avec des données corrélées : application à des données génomiques : Methods for staistical inference on correlated data : application to genomic data.

Degree: Docteur es, Physique, 2015, Paris, Ecole normale supérieure

La disponibilité de quantités énormes de données a changé le rôle de la physique par rapport aux autres disciplines. Dans cette thèse, je vais explorer… (more)

Subjects/Keywords: Inférence; ARN; Champ moyen; Modèl de Potts; Modèles génératifs; Régularisation; Prédiction structurelle; Inference; RNA; Mean-field; Potts model; Generative models; Regularisation; Structure prediction; 530

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APA (6th Edition):

Leonardis, E. D. (2015). Méthodes pour l'inférence en grande dimension avec des données corrélées : application à des données génomiques : Methods for staistical inference on correlated data : application to genomic data. (Doctoral Dissertation). Paris, Ecole normale supérieure. Retrieved from http://www.theses.fr/2015ENSU0033

Chicago Manual of Style (16th Edition):

Leonardis, Eleonora De. “Méthodes pour l'inférence en grande dimension avec des données corrélées : application à des données génomiques : Methods for staistical inference on correlated data : application to genomic data.” 2015. Doctoral Dissertation, Paris, Ecole normale supérieure. Accessed November 19, 2019. http://www.theses.fr/2015ENSU0033.

MLA Handbook (7th Edition):

Leonardis, Eleonora De. “Méthodes pour l'inférence en grande dimension avec des données corrélées : application à des données génomiques : Methods for staistical inference on correlated data : application to genomic data.” 2015. Web. 19 Nov 2019.

Vancouver:

Leonardis ED. Méthodes pour l'inférence en grande dimension avec des données corrélées : application à des données génomiques : Methods for staistical inference on correlated data : application to genomic data. [Internet] [Doctoral dissertation]. Paris, Ecole normale supérieure; 2015. [cited 2019 Nov 19]. Available from: http://www.theses.fr/2015ENSU0033.

Council of Science Editors:

Leonardis ED. Méthodes pour l'inférence en grande dimension avec des données corrélées : application à des données génomiques : Methods for staistical inference on correlated data : application to genomic data. [Doctoral Dissertation]. Paris, Ecole normale supérieure; 2015. Available from: http://www.theses.fr/2015ENSU0033

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