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You searched for +publisher:"University of North Carolina" +contributor:("Tropsha, Alexander"). Showing records 1 – 21 of 21 total matches.

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University of North Carolina

1. Zhao, Guiyu. The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors.

Degree: 2011, University of North Carolina

 Recent advances in High Throughput Screening (HTS) led to the rapid growth of chemical libraries of small molecules, which calls for improved computational tools and… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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

APA (6th Edition):

Zhao, G. (2011). The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:fcfac6e3-eebd-4e55-95da-ae3915eb7df9

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):

Zhao, Guiyu. “The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors.” 2011. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:fcfac6e3-eebd-4e55-95da-ae3915eb7df9.

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

MLA Handbook (7th Edition):

Zhao, Guiyu. “The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors.” 2011. Web. 24 Nov 2020.

Vancouver:

Zhao G. The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:fcfac6e3-eebd-4e55-95da-ae3915eb7df9.

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

Council of Science Editors:

Zhao G. The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:fcfac6e3-eebd-4e55-95da-ae3915eb7df9

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


University of North Carolina

2. Kietsakorn, Tanarat. Protein function prediction using family-specific structural motifs.

Degree: 2011, University of North Carolina

 Protein function prediction using structural motifs is expected to be more reliable and informative than using global sequences/structures or sequence motifs. In the first part… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Kietsakorn, T. (2011). Protein function prediction using family-specific structural motifs. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:fa1a377e-327b-4e50-842b-47d40a8bea63

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):

Kietsakorn, Tanarat. “Protein function prediction using family-specific structural motifs.” 2011. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:fa1a377e-327b-4e50-842b-47d40a8bea63.

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

MLA Handbook (7th Edition):

Kietsakorn, Tanarat. “Protein function prediction using family-specific structural motifs.” 2011. Web. 24 Nov 2020.

Vancouver:

Kietsakorn T. Protein function prediction using family-specific structural motifs. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:fa1a377e-327b-4e50-842b-47d40a8bea63.

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

Council of Science Editors:

Kietsakorn T. Protein function prediction using family-specific structural motifs. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:fa1a377e-327b-4e50-842b-47d40a8bea63

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


University of North Carolina

3. Hao. Prioritizing Small Molecules for Drug Discovery or Chemical Safety Assessments using Ligand- and Structure-based Cheminformatics Approaches.

Degree: Biochemistry and Biophysics, 2011, University of North Carolina

 Recent growth in the experimental data describing the effects of chemicals at the molecular, cellular, and organism level has triggered the development of novel computational… (more)

Subjects/Keywords: School of Medicine; Department of Biochemistry and Biophysics

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APA (6th Edition):

Hao. (2011). Prioritizing Small Molecules for Drug Discovery or Chemical Safety Assessments using Ligand- and Structure-based Cheminformatics Approaches. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:69fb5fff-a718-4d8d-86b9-bde0f6744252

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

Chicago Manual of Style (16th Edition):

Hao. “Prioritizing Small Molecules for Drug Discovery or Chemical Safety Assessments using Ligand- and Structure-based Cheminformatics Approaches.” 2011. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:69fb5fff-a718-4d8d-86b9-bde0f6744252.

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

MLA Handbook (7th Edition):

Hao. “Prioritizing Small Molecules for Drug Discovery or Chemical Safety Assessments using Ligand- and Structure-based Cheminformatics Approaches.” 2011. Web. 24 Nov 2020.

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

Vancouver:

Hao. Prioritizing Small Molecules for Drug Discovery or Chemical Safety Assessments using Ligand- and Structure-based Cheminformatics Approaches. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:69fb5fff-a718-4d8d-86b9-bde0f6744252.

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

Council of Science Editors:

Hao. Prioritizing Small Molecules for Drug Discovery or Chemical Safety Assessments using Ligand- and Structure-based Cheminformatics Approaches. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:69fb5fff-a718-4d8d-86b9-bde0f6744252

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


University of North Carolina

4. Pu, Dongqiuye. Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles.

Degree: 2012, University of North Carolina

 Safety issues are considered the single largest reason for today’s drug development failures. It is both costly and time-consuming for toxicological evaluation of materials. This… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Pharmacoengineering and Molecular Pharmaceutics

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APA (6th Edition):

Pu, D. (2012). Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:a660ee98-4916-420c-9eb2-60b139eecd80

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):

Pu, Dongqiuye. “Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles.” 2012. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:a660ee98-4916-420c-9eb2-60b139eecd80.

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

MLA Handbook (7th Edition):

Pu, Dongqiuye. “Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles.” 2012. Web. 24 Nov 2020.

Vancouver:

Pu D. Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles. [Internet] [Thesis]. University of North Carolina; 2012. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:a660ee98-4916-420c-9eb2-60b139eecd80.

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

Council of Science Editors:

Pu D. Quantitative structure-toxicity relationship modeling of organic compounds and nanoparticles. [Thesis]. University of North Carolina; 2012. Available from: https://cdr.lib.unc.edu/record/uuid:a660ee98-4916-420c-9eb2-60b139eecd80

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


University of North Carolina

5. Grulke, Christopher M. Development and Extension of Cheminformatics Techniques for Integration of Diverse Data to Enhance Drug Discovery.

Degree: 2011, University of North Carolina

 The scientific community has fallen headlong into the age of data. With the available crop of information available to scientists growing at an exponential pace,… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Grulke, C. M. (2011). Development and Extension of Cheminformatics Techniques for Integration of Diverse Data to Enhance Drug Discovery. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:61606aa0-f1da-41cc-a6f7-e3405930ee75

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):

Grulke, Christopher M. “Development and Extension of Cheminformatics Techniques for Integration of Diverse Data to Enhance Drug Discovery.” 2011. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:61606aa0-f1da-41cc-a6f7-e3405930ee75.

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

MLA Handbook (7th Edition):

Grulke, Christopher M. “Development and Extension of Cheminformatics Techniques for Integration of Diverse Data to Enhance Drug Discovery.” 2011. Web. 24 Nov 2020.

Vancouver:

Grulke CM. Development and Extension of Cheminformatics Techniques for Integration of Diverse Data to Enhance Drug Discovery. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:61606aa0-f1da-41cc-a6f7-e3405930ee75.

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

Council of Science Editors:

Grulke CM. Development and Extension of Cheminformatics Techniques for Integration of Diverse Data to Enhance Drug Discovery. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:61606aa0-f1da-41cc-a6f7-e3405930ee75

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


University of North Carolina

6. Bush, Stephen James. SNAPP, CRACLe, PoPP: Predicting Protein Interactions.

Degree: 2014, University of North Carolina

 Protein-Protein Interactions (PPIs) play a central role in all major signaling events that occur in living cells, from DNA replication to complex, post-translational protein-signaling systems.… (more)

Subjects/Keywords: School of Medicine; Curriculum in Bioinformatics and Computational Biology

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APA (6th Edition):

Bush, S. J. (2014). SNAPP, CRACLe, PoPP: Predicting Protein Interactions. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:51a81011-a679-48e7-87e1-79af18481a74

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):

Bush, Stephen James. “SNAPP, CRACLe, PoPP: Predicting Protein Interactions.” 2014. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:51a81011-a679-48e7-87e1-79af18481a74.

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

MLA Handbook (7th Edition):

Bush, Stephen James. “SNAPP, CRACLe, PoPP: Predicting Protein Interactions.” 2014. Web. 24 Nov 2020.

Vancouver:

Bush SJ. SNAPP, CRACLe, PoPP: Predicting Protein Interactions. [Internet] [Thesis]. University of North Carolina; 2014. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:51a81011-a679-48e7-87e1-79af18481a74.

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

Council of Science Editors:

Bush SJ. SNAPP, CRACLe, PoPP: Predicting Protein Interactions. [Thesis]. University of North Carolina; 2014. Available from: https://cdr.lib.unc.edu/record/uuid:51a81011-a679-48e7-87e1-79af18481a74

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


University of North Carolina

7. Low, Yen Sia. Toxicity prediction using multi-disciplinary data integration and novel computational approaches.

Degree: Environmental Sciences and Engineering, 2013, University of North Carolina

 Current predictive tools used for human health assessment of potential chemical hazards rely primarily on either chemical structural information (i.e., cheminformatics) or bioassay data (i.e.,… (more)

Subjects/Keywords: Gillings School of Global Public Health; Department of Environmental Sciences and Engineering

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APA (6th Edition):

Low, Y. S. (2013). Toxicity prediction using multi-disciplinary data integration and novel computational approaches. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:37864ace-5cda-4f4e-996e-b0a4bb2cceab

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):

Low, Yen Sia. “Toxicity prediction using multi-disciplinary data integration and novel computational approaches.” 2013. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:37864ace-5cda-4f4e-996e-b0a4bb2cceab.

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

MLA Handbook (7th Edition):

Low, Yen Sia. “Toxicity prediction using multi-disciplinary data integration and novel computational approaches.” 2013. Web. 24 Nov 2020.

Vancouver:

Low YS. Toxicity prediction using multi-disciplinary data integration and novel computational approaches. [Internet] [Thesis]. University of North Carolina; 2013. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:37864ace-5cda-4f4e-996e-b0a4bb2cceab.

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

Council of Science Editors:

Low YS. Toxicity prediction using multi-disciplinary data integration and novel computational approaches. [Thesis]. University of North Carolina; 2013. Available from: https://cdr.lib.unc.edu/record/uuid:37864ace-5cda-4f4e-996e-b0a4bb2cceab

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


University of North Carolina

8. Hsieh, Jui-Hua. Cheminformatics Approaches to Structure Based Virtual Screening: Methodology Development and Applications.

Degree: 2011, University of North Carolina

 Structure-based virtual screening (VS) using 3D structures of protein targets has become a popular in silico drug discovery approach. The success of VS relies on… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Hsieh, J. (2011). Cheminformatics Approaches to Structure Based Virtual Screening: Methodology Development and Applications. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:90ecfe4a-a4b0-4559-a431-b68c05ad4c50

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):

Hsieh, Jui-Hua. “Cheminformatics Approaches to Structure Based Virtual Screening: Methodology Development and Applications.” 2011. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:90ecfe4a-a4b0-4559-a431-b68c05ad4c50.

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

MLA Handbook (7th Edition):

Hsieh, Jui-Hua. “Cheminformatics Approaches to Structure Based Virtual Screening: Methodology Development and Applications.” 2011. Web. 24 Nov 2020.

Vancouver:

Hsieh J. Cheminformatics Approaches to Structure Based Virtual Screening: Methodology Development and Applications. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:90ecfe4a-a4b0-4559-a431-b68c05ad4c50.

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

Council of Science Editors:

Hsieh J. Cheminformatics Approaches to Structure Based Virtual Screening: Methodology Development and Applications. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:90ecfe4a-a4b0-4559-a431-b68c05ad4c50

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


University of North Carolina

9. Hajjo, Rima M. K. I. In silico strategies to study polypharmacology of G-protein-coupled receptors.

Degree: 2010, University of North Carolina

 The development of drugs that simultaneously target multiple receptors in a rational way (i.e., 'magic shotguns') is regarded as a promising approach for drug discovery… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Hajjo, R. M. K. I. (2010). In silico strategies to study polypharmacology of G-protein-coupled receptors. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:03c0bbab-2a4a-49b3-8963-a38317e244e6

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):

Hajjo, Rima M K I. “In silico strategies to study polypharmacology of G-protein-coupled receptors.” 2010. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:03c0bbab-2a4a-49b3-8963-a38317e244e6.

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

MLA Handbook (7th Edition):

Hajjo, Rima M K I. “In silico strategies to study polypharmacology of G-protein-coupled receptors.” 2010. Web. 24 Nov 2020.

Vancouver:

Hajjo RMKI. In silico strategies to study polypharmacology of G-protein-coupled receptors. [Internet] [Thesis]. University of North Carolina; 2010. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:03c0bbab-2a4a-49b3-8963-a38317e244e6.

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

Council of Science Editors:

Hajjo RMKI. In silico strategies to study polypharmacology of G-protein-coupled receptors. [Thesis]. University of North Carolina; 2010. Available from: https://cdr.lib.unc.edu/record/uuid:03c0bbab-2a4a-49b3-8963-a38317e244e6

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


University of North Carolina

10. Luo, Man. Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules.

Degree: 2011, University of North Carolina

 Ligand-based drug design is a popular and efficient computational approach to facilitate the drug discovery process. Current approaches mainly focus on optimizing the computational algorithms… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Luo, M. (2011). Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:5d04db2a-60e2-42dd-8ac3-c9c3e4a8af6e

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):

Luo, Man. “Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules.” 2011. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:5d04db2a-60e2-42dd-8ac3-c9c3e4a8af6e.

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

MLA Handbook (7th Edition):

Luo, Man. “Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules.” 2011. Web. 24 Nov 2020.

Vancouver:

Luo M. Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules. [Internet] [Thesis]. University of North Carolina; 2011. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:5d04db2a-60e2-42dd-8ac3-c9c3e4a8af6e.

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

Council of Science Editors:

Luo M. Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules. [Thesis]. University of North Carolina; 2011. Available from: https://cdr.lib.unc.edu/record/uuid:5d04db2a-60e2-42dd-8ac3-c9c3e4a8af6e

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


University of North Carolina

11. Ainslie, Garrett Robert. A Translational Approach to Assess the Risk of Dietary Substance-Drug Interactions.

Degree: 2015, University of North Carolina

 Myriad diet-derived substances, including foods, nutritional supplements, and exotic beverages are increasingly sought for their purported health benefits. These natural, seemingly safe, products can perpetrate… (more)

Subjects/Keywords: Toxicology; Pharmaceutical chemistry; School of Medicine; Curriculum in Toxicology

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APA (6th Edition):

Ainslie, G. R. (2015). A Translational Approach to Assess the Risk of Dietary Substance-Drug Interactions. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:cfbcab30-f537-46fd-b7bc-cf1e5f4cbefa

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):

Ainslie, Garrett Robert. “A Translational Approach to Assess the Risk of Dietary Substance-Drug Interactions.” 2015. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:cfbcab30-f537-46fd-b7bc-cf1e5f4cbefa.

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

MLA Handbook (7th Edition):

Ainslie, Garrett Robert. “A Translational Approach to Assess the Risk of Dietary Substance-Drug Interactions.” 2015. Web. 24 Nov 2020.

Vancouver:

Ainslie GR. A Translational Approach to Assess the Risk of Dietary Substance-Drug Interactions. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:cfbcab30-f537-46fd-b7bc-cf1e5f4cbefa.

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

Council of Science Editors:

Ainslie GR. A Translational Approach to Assess the Risk of Dietary Substance-Drug Interactions. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:cfbcab30-f537-46fd-b7bc-cf1e5f4cbefa

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


University of North Carolina

12. Claypool, Sarah. Characterization and Application of Highly Specific 2’-F RNA Aptamers Targeting a Potentially Novel Pancreatic Ductal Adenocarcinoma (PDAC) Biomarker(s).

Degree: 2015, University of North Carolina

 Pancreatic ductal adenocarcinoma (PDAC) has an extremely dismal 5-year survival rate of only 6%. Highly specific targeting ligands that can aid in early stage diagnosis… (more)

Subjects/Keywords: Pharmaceutical chemistry; Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Claypool, S. (2015). Characterization and Application of Highly Specific 2’-F RNA Aptamers Targeting a Potentially Novel Pancreatic Ductal Adenocarcinoma (PDAC) Biomarker(s). (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:afa50fb2-a331-4191-96f0-5b849aa7a9fc

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):

Claypool, Sarah. “Characterization and Application of Highly Specific 2’-F RNA Aptamers Targeting a Potentially Novel Pancreatic Ductal Adenocarcinoma (PDAC) Biomarker(s).” 2015. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:afa50fb2-a331-4191-96f0-5b849aa7a9fc.

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

MLA Handbook (7th Edition):

Claypool, Sarah. “Characterization and Application of Highly Specific 2’-F RNA Aptamers Targeting a Potentially Novel Pancreatic Ductal Adenocarcinoma (PDAC) Biomarker(s).” 2015. Web. 24 Nov 2020.

Vancouver:

Claypool S. Characterization and Application of Highly Specific 2’-F RNA Aptamers Targeting a Potentially Novel Pancreatic Ductal Adenocarcinoma (PDAC) Biomarker(s). [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:afa50fb2-a331-4191-96f0-5b849aa7a9fc.

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

Council of Science Editors:

Claypool S. Characterization and Application of Highly Specific 2’-F RNA Aptamers Targeting a Potentially Novel Pancreatic Ductal Adenocarcinoma (PDAC) Biomarker(s). [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:afa50fb2-a331-4191-96f0-5b849aa7a9fc

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


University of North Carolina

13. Jacobs, Tim. De Novo Proteins Designed From Evolutionary Principles.

Degree: 2015, University of North Carolina

 Protein engineering has rapidly developed into a powerful method for the optimization, alteration, and creation of protein functions. Current protein engineering methods fall into the… (more)

Subjects/Keywords: Biochemistry; Bioinformatics; School of Medicine; Curriculum in Bioinformatics and Computational Biology

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APA (6th Edition):

Jacobs, T. (2015). De Novo Proteins Designed From Evolutionary Principles. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:e5c99a71-24d2-46bc-bbfe-4ff6c8607fa5

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):

Jacobs, Tim. “De Novo Proteins Designed From Evolutionary Principles.” 2015. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:e5c99a71-24d2-46bc-bbfe-4ff6c8607fa5.

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

MLA Handbook (7th Edition):

Jacobs, Tim. “De Novo Proteins Designed From Evolutionary Principles.” 2015. Web. 24 Nov 2020.

Vancouver:

Jacobs T. De Novo Proteins Designed From Evolutionary Principles. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:e5c99a71-24d2-46bc-bbfe-4ff6c8607fa5.

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

Council of Science Editors:

Jacobs T. De Novo Proteins Designed From Evolutionary Principles. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:e5c99a71-24d2-46bc-bbfe-4ff6c8607fa5

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


University of North Carolina

14. Fant, Andrew. The Effect of Data Curation on the Accuracy of Quantitative Structure-Activity Relationship Models.

Degree: 2015, University of North Carolina

 In the 33 years since the first public release of GenBank, and the 15 years since the publication of the first pilot assembly of the… (more)

Subjects/Keywords: Pharmaceutical chemistry; Chemistry; Pharmacology; Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Fant, A. (2015). The Effect of Data Curation on the Accuracy of Quantitative Structure-Activity Relationship Models. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:fc71a688-33be-402d-a99d-3d1c75efe86d

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):

Fant, Andrew. “The Effect of Data Curation on the Accuracy of Quantitative Structure-Activity Relationship Models.” 2015. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:fc71a688-33be-402d-a99d-3d1c75efe86d.

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

MLA Handbook (7th Edition):

Fant, Andrew. “The Effect of Data Curation on the Accuracy of Quantitative Structure-Activity Relationship Models.” 2015. Web. 24 Nov 2020.

Vancouver:

Fant A. The Effect of Data Curation on the Accuracy of Quantitative Structure-Activity Relationship Models. [Internet] [Thesis]. University of North Carolina; 2015. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:fc71a688-33be-402d-a99d-3d1c75efe86d.

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

Council of Science Editors:

Fant A. The Effect of Data Curation on the Accuracy of Quantitative Structure-Activity Relationship Models. [Thesis]. University of North Carolina; 2015. Available from: https://cdr.lib.unc.edu/record/uuid:fc71a688-33be-402d-a99d-3d1c75efe86d

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


University of North Carolina

15. Wang, Kun. Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets.

Degree: 2010, University of North Carolina

 Imbalanced dataset mining is a nontrivial issue. It has extensive applications in a variety of fields, such as scientific research, medical diagnosis, business, multiple industries,… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Wang, K. (2010). Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:87a64bfc-38f3-43d3-8b27-b3f97cebdd2a

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):

Wang, Kun. “Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets.” 2010. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:87a64bfc-38f3-43d3-8b27-b3f97cebdd2a.

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

MLA Handbook (7th Edition):

Wang, Kun. “Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets.” 2010. Web. 24 Nov 2020.

Vancouver:

Wang K. Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets. [Internet] [Thesis]. University of North Carolina; 2010. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:87a64bfc-38f3-43d3-8b27-b3f97cebdd2a.

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

Council of Science Editors:

Wang K. Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets. [Thesis]. University of North Carolina; 2010. Available from: https://cdr.lib.unc.edu/record/uuid:87a64bfc-38f3-43d3-8b27-b3f97cebdd2a

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


University of North Carolina

16. Goliaei, Ardeshir. Poration of Biological Membranes by Antimicrobial Peptides and Pressure, Insights from Computer Simulations.

Degree: Biochemistry and Biophysics, 2016, University of North Carolina

 The plasma membrane is the boundary of the cell that separates the outside world from its interior. It is the first barrier that any exogenous… (more)

Subjects/Keywords: School of Medicine; Department of Biochemistry and Biophysics

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APA (6th Edition):

Goliaei, A. (2016). Poration of Biological Membranes by Antimicrobial Peptides and Pressure, Insights from Computer Simulations. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:a09d0ebb-b2bb-4512-afaa-941cf5996d52

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):

Goliaei, Ardeshir. “Poration of Biological Membranes by Antimicrobial Peptides and Pressure, Insights from Computer Simulations.” 2016. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:a09d0ebb-b2bb-4512-afaa-941cf5996d52.

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

MLA Handbook (7th Edition):

Goliaei, Ardeshir. “Poration of Biological Membranes by Antimicrobial Peptides and Pressure, Insights from Computer Simulations.” 2016. Web. 24 Nov 2020.

Vancouver:

Goliaei A. Poration of Biological Membranes by Antimicrobial Peptides and Pressure, Insights from Computer Simulations. [Internet] [Thesis]. University of North Carolina; 2016. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:a09d0ebb-b2bb-4512-afaa-941cf5996d52.

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

Council of Science Editors:

Goliaei A. Poration of Biological Membranes by Antimicrobial Peptides and Pressure, Insights from Computer Simulations. [Thesis]. University of North Carolina; 2016. Available from: https://cdr.lib.unc.edu/record/uuid:a09d0ebb-b2bb-4512-afaa-941cf5996d52

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


University of North Carolina

17. Capuzzi, Stephen. PREDICTIVE CHEMINFORMATICS ANALYSIS OF DIVERSE CHEMOGENOMICS DATA SOURCES: APPLICATIONS TO DRUG DISCOVERY, ASSAY INTERFERENCE, AND TEXT MINING.

Degree: 2018, University of North Carolina

 In this dissertation, we describe the cheminformatics analysis of diverse chemogenomics data sources as well as the application of these data to several drug discovery… (more)

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APA (6th Edition):

Capuzzi, S. (2018). PREDICTIVE CHEMINFORMATICS ANALYSIS OF DIVERSE CHEMOGENOMICS DATA SOURCES: APPLICATIONS TO DRUG DISCOVERY, ASSAY INTERFERENCE, AND TEXT MINING. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:4d622f01-7f80-4055-8206-73fccd2eef6d

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):

Capuzzi, Stephen. “PREDICTIVE CHEMINFORMATICS ANALYSIS OF DIVERSE CHEMOGENOMICS DATA SOURCES: APPLICATIONS TO DRUG DISCOVERY, ASSAY INTERFERENCE, AND TEXT MINING.” 2018. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:4d622f01-7f80-4055-8206-73fccd2eef6d.

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

MLA Handbook (7th Edition):

Capuzzi, Stephen. “PREDICTIVE CHEMINFORMATICS ANALYSIS OF DIVERSE CHEMOGENOMICS DATA SOURCES: APPLICATIONS TO DRUG DISCOVERY, ASSAY INTERFERENCE, AND TEXT MINING.” 2018. Web. 24 Nov 2020.

Vancouver:

Capuzzi S. PREDICTIVE CHEMINFORMATICS ANALYSIS OF DIVERSE CHEMOGENOMICS DATA SOURCES: APPLICATIONS TO DRUG DISCOVERY, ASSAY INTERFERENCE, AND TEXT MINING. [Internet] [Thesis]. University of North Carolina; 2018. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:4d622f01-7f80-4055-8206-73fccd2eef6d.

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

Council of Science Editors:

Capuzzi S. PREDICTIVE CHEMINFORMATICS ANALYSIS OF DIVERSE CHEMOGENOMICS DATA SOURCES: APPLICATIONS TO DRUG DISCOVERY, ASSAY INTERFERENCE, AND TEXT MINING. [Thesis]. University of North Carolina; 2018. Available from: https://cdr.lib.unc.edu/record/uuid:4d622f01-7f80-4055-8206-73fccd2eef6d

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


University of North Carolina

18. Khashan, Raed Saeed. Developmment and Application of Ligand-based and Structure-based Computational Drug Discovery Tools Based on Frequent Subgraph Mining of Chemical Structures.

Degree: 2007, University of North Carolina

 Recent development in subgraph mining tools resulted in faster and more efficient algorithms that facilitate exploring the information encoded in data that can be represented… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Khashan, R. S. (2007). Developmment and Application of Ligand-based and Structure-based Computational Drug Discovery Tools Based on Frequent Subgraph Mining of Chemical Structures. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:d4a6eda2-935b-483a-81b3-ff6030aae800

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):

Khashan, Raed Saeed. “Developmment and Application of Ligand-based and Structure-based Computational Drug Discovery Tools Based on Frequent Subgraph Mining of Chemical Structures.” 2007. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:d4a6eda2-935b-483a-81b3-ff6030aae800.

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

MLA Handbook (7th Edition):

Khashan, Raed Saeed. “Developmment and Application of Ligand-based and Structure-based Computational Drug Discovery Tools Based on Frequent Subgraph Mining of Chemical Structures.” 2007. Web. 24 Nov 2020.

Vancouver:

Khashan RS. Developmment and Application of Ligand-based and Structure-based Computational Drug Discovery Tools Based on Frequent Subgraph Mining of Chemical Structures. [Internet] [Thesis]. University of North Carolina; 2007. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:d4a6eda2-935b-483a-81b3-ff6030aae800.

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

Council of Science Editors:

Khashan RS. Developmment and Application of Ligand-based and Structure-based Computational Drug Discovery Tools Based on Frequent Subgraph Mining of Chemical Structures. [Thesis]. University of North Carolina; 2007. Available from: https://cdr.lib.unc.edu/record/uuid:d4a6eda2-935b-483a-81b3-ff6030aae800

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


University of North Carolina

19. Flanagan, Keri. Evaluation of Potential Inhibitors of Escherichia coli RecA to Attenuate the Rate of Antibiotic Resistance Development and to Sensitize Escherichia coli to Current Antibiotics.

Degree: 2009, University of North Carolina

 Antibacterials are invaluable to treating infectious diseases. However, bacteria have a profound ability to alter their susceptibility to antibiotics, rendering themselves resistant to one or… (more)

Subjects/Keywords: Eshelman School of Pharmacy; Division of Chemical Biology and Medicinal Chemistry

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APA (6th Edition):

Flanagan, K. (2009). Evaluation of Potential Inhibitors of Escherichia coli RecA to Attenuate the Rate of Antibiotic Resistance Development and to Sensitize Escherichia coli to Current Antibiotics. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:ed67cc4f-aaab-48bb-9420-164a59b1a219

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):

Flanagan, Keri. “Evaluation of Potential Inhibitors of Escherichia coli RecA to Attenuate the Rate of Antibiotic Resistance Development and to Sensitize Escherichia coli to Current Antibiotics.” 2009. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:ed67cc4f-aaab-48bb-9420-164a59b1a219.

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

MLA Handbook (7th Edition):

Flanagan, Keri. “Evaluation of Potential Inhibitors of Escherichia coli RecA to Attenuate the Rate of Antibiotic Resistance Development and to Sensitize Escherichia coli to Current Antibiotics.” 2009. Web. 24 Nov 2020.

Vancouver:

Flanagan K. Evaluation of Potential Inhibitors of Escherichia coli RecA to Attenuate the Rate of Antibiotic Resistance Development and to Sensitize Escherichia coli to Current Antibiotics. [Internet] [Thesis]. University of North Carolina; 2009. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:ed67cc4f-aaab-48bb-9420-164a59b1a219.

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

Council of Science Editors:

Flanagan K. Evaluation of Potential Inhibitors of Escherichia coli RecA to Attenuate the Rate of Antibiotic Resistance Development and to Sensitize Escherichia coli to Current Antibiotics. [Thesis]. University of North Carolina; 2009. Available from: https://cdr.lib.unc.edu/record/uuid:ed67cc4f-aaab-48bb-9420-164a59b1a219

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


University of North Carolina

20. Chen, Yetian. Spatial motif discovery in papain-like cysteine protease family.

Degree: Biochemistry and Biophysics, 2008, University of North Carolina

 Spatial motifs, which are amino acid packing patterns, occur frequently within a set of proteins with some common specific functions and features. In this study,… (more)

Subjects/Keywords: School of Medicine; Department of Biochemistry and Biophysics

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APA (6th Edition):

Chen, Y. (2008). Spatial motif discovery in papain-like cysteine protease family. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:eb0d61ef-bfb9-4de8-8452-86b8d8199a29

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, Yetian. “Spatial motif discovery in papain-like cysteine protease family.” 2008. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:eb0d61ef-bfb9-4de8-8452-86b8d8199a29.

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

MLA Handbook (7th Edition):

Chen, Yetian. “Spatial motif discovery in papain-like cysteine protease family.” 2008. Web. 24 Nov 2020.

Vancouver:

Chen Y. Spatial motif discovery in papain-like cysteine protease family. [Internet] [Thesis]. University of North Carolina; 2008. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:eb0d61ef-bfb9-4de8-8452-86b8d8199a29.

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

Council of Science Editors:

Chen Y. Spatial motif discovery in papain-like cysteine protease family. [Thesis]. University of North Carolina; 2008. Available from: https://cdr.lib.unc.edu/record/uuid:eb0d61ef-bfb9-4de8-8452-86b8d8199a29

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


University of North Carolina

21. Bautz, David. Identification of Protein's Complementary to the Autoantigen Proteinase 3 and Their Involvement in the Pathogenesis of Autoimmune Disease.

Degree: Biochemistry and Biophysics, 2008, University of North Carolina

 Previous work by our research group showed that PR3-ANCA patients had an antibody response to a recombinant complementary-PR3 protein encoded by the antisense strand of… (more)

Subjects/Keywords: School of Medicine; Department of Biochemistry and Biophysics

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APA (6th Edition):

Bautz, D. (2008). Identification of Protein's Complementary to the Autoantigen Proteinase 3 and Their Involvement in the Pathogenesis of Autoimmune Disease. (Thesis). University of North Carolina. Retrieved from https://cdr.lib.unc.edu/record/uuid:1374ff2f-0fd4-43b3-8a33-324385ebae01

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):

Bautz, David. “Identification of Protein's Complementary to the Autoantigen Proteinase 3 and Their Involvement in the Pathogenesis of Autoimmune Disease.” 2008. Thesis, University of North Carolina. Accessed November 24, 2020. https://cdr.lib.unc.edu/record/uuid:1374ff2f-0fd4-43b3-8a33-324385ebae01.

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

MLA Handbook (7th Edition):

Bautz, David. “Identification of Protein's Complementary to the Autoantigen Proteinase 3 and Their Involvement in the Pathogenesis of Autoimmune Disease.” 2008. Web. 24 Nov 2020.

Vancouver:

Bautz D. Identification of Protein's Complementary to the Autoantigen Proteinase 3 and Their Involvement in the Pathogenesis of Autoimmune Disease. [Internet] [Thesis]. University of North Carolina; 2008. [cited 2020 Nov 24]. Available from: https://cdr.lib.unc.edu/record/uuid:1374ff2f-0fd4-43b3-8a33-324385ebae01.

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

Council of Science Editors:

Bautz D. Identification of Protein's Complementary to the Autoantigen Proteinase 3 and Their Involvement in the Pathogenesis of Autoimmune Disease. [Thesis]. University of North Carolina; 2008. Available from: https://cdr.lib.unc.edu/record/uuid:1374ff2f-0fd4-43b3-8a33-324385ebae01

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

.