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You searched for subject:(biological networks). Showing records 1 – 30 of 141 total matches.

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University of Sydney

1. McGrane, Martin. Biological Network Distances .

Degree: 2016, University of Sydney

Networks of interactions are increasingly used to model biological systems. The patterns of these networks capture a larger, more complex, representation of the whole than… (more)

Subjects/Keywords: bNED; biological networks

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APA (6th Edition):

McGrane, M. (2016). Biological Network Distances . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/17233

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):

McGrane, Martin. “Biological Network Distances .” 2016. Thesis, University of Sydney. Accessed December 13, 2019. http://hdl.handle.net/2123/17233.

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

MLA Handbook (7th Edition):

McGrane, Martin. “Biological Network Distances .” 2016. Web. 13 Dec 2019.

Vancouver:

McGrane M. Biological Network Distances . [Internet] [Thesis]. University of Sydney; 2016. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/2123/17233.

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

Council of Science Editors:

McGrane M. Biological Network Distances . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/17233

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

2. Galeano, J. A structural approach to disentangle the visualization of bipartite biological networks.

Degree: 2018, Complexity

Subjects/Keywords: Biological networks

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APA (6th Edition):

Galeano, J. (2018). A structural approach to disentangle the visualization of bipartite biological networks. (Thesis). Complexity. Retrieved from http://hdl.handle.net/10641/1452

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):

Galeano, J. “A structural approach to disentangle the visualization of bipartite biological networks.” 2018. Thesis, Complexity. Accessed December 13, 2019. http://hdl.handle.net/10641/1452.

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

MLA Handbook (7th Edition):

Galeano, J. “A structural approach to disentangle the visualization of bipartite biological networks.” 2018. Web. 13 Dec 2019.

Vancouver:

Galeano J. A structural approach to disentangle the visualization of bipartite biological networks. [Internet] [Thesis]. Complexity; 2018. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/10641/1452.

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

Council of Science Editors:

Galeano J. A structural approach to disentangle the visualization of bipartite biological networks. [Thesis]. Complexity; 2018. Available from: http://hdl.handle.net/10641/1452

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


Virginia Commonwealth University

3. Thomas, Sterling. A Novel Method to Detect Functional Subgraphs in Biomolecular Networks.

Degree: PhD, Integrative Life Sciences, 2010, Virginia Commonwealth University

 Several biomolecular pathways governing the control of cellular processes have been discovered over the last several years. Additionally, advances resulting from combining these pathways into… (more)

Subjects/Keywords: Biological Networks; Bioinformatics; Life Sciences

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APA (6th Edition):

Thomas, S. (2010). A Novel Method to Detect Functional Subgraphs in Biomolecular Networks. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/154

Chicago Manual of Style (16th Edition):

Thomas, Sterling. “A Novel Method to Detect Functional Subgraphs in Biomolecular Networks.” 2010. Doctoral Dissertation, Virginia Commonwealth University. Accessed December 13, 2019. https://scholarscompass.vcu.edu/etd/154.

MLA Handbook (7th Edition):

Thomas, Sterling. “A Novel Method to Detect Functional Subgraphs in Biomolecular Networks.” 2010. Web. 13 Dec 2019.

Vancouver:

Thomas S. A Novel Method to Detect Functional Subgraphs in Biomolecular Networks. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2010. [cited 2019 Dec 13]. Available from: https://scholarscompass.vcu.edu/etd/154.

Council of Science Editors:

Thomas S. A Novel Method to Detect Functional Subgraphs in Biomolecular Networks. [Doctoral Dissertation]. Virginia Commonwealth University; 2010. Available from: https://scholarscompass.vcu.edu/etd/154


University of Victoria

4. Quee, Graham. Ramp approximations of finitely steep sigmoid control functions in soft-switching ODE networks.

Degree: Department of Mathematics and Statistics, 2019, University of Victoria

 In models for networks of regulatory interactions in biological molecules, the sigmoid relationship between concentration of regulating bodies and the production rates they control has… (more)

Subjects/Keywords: Glass Networks; ODE; Gene regulation; Biological Regulation; Biological models; switching networks

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APA (6th Edition):

Quee, G. (2019). Ramp approximations of finitely steep sigmoid control functions in soft-switching ODE networks. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/10746

Chicago Manual of Style (16th Edition):

Quee, Graham. “Ramp approximations of finitely steep sigmoid control functions in soft-switching ODE networks.” 2019. Masters Thesis, University of Victoria. Accessed December 13, 2019. http://hdl.handle.net/1828/10746.

MLA Handbook (7th Edition):

Quee, Graham. “Ramp approximations of finitely steep sigmoid control functions in soft-switching ODE networks.” 2019. Web. 13 Dec 2019.

Vancouver:

Quee G. Ramp approximations of finitely steep sigmoid control functions in soft-switching ODE networks. [Internet] [Masters thesis]. University of Victoria; 2019. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/1828/10746.

Council of Science Editors:

Quee G. Ramp approximations of finitely steep sigmoid control functions in soft-switching ODE networks. [Masters Thesis]. University of Victoria; 2019. Available from: http://hdl.handle.net/1828/10746


University of Minnesota

5. Koch, Elizabeth. Computational analysis of genetic interaction network structures and gene properties.

Degree: PhD, Computer Science, 2017, University of Minnesota

 Cellular systems are responsible for many complex tasks, such as carrying out cell cycle phases, responding to intra- and extra-cellular conditions, and resolving errors. Through… (more)

Subjects/Keywords: Biological networks; Genetic interactions; Genomics; Pleiotropy; Yeast

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APA (6th Edition):

Koch, E. (2017). Computational analysis of genetic interaction network structures and gene properties. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/190545

Chicago Manual of Style (16th Edition):

Koch, Elizabeth. “Computational analysis of genetic interaction network structures and gene properties.” 2017. Doctoral Dissertation, University of Minnesota. Accessed December 13, 2019. http://hdl.handle.net/11299/190545.

MLA Handbook (7th Edition):

Koch, Elizabeth. “Computational analysis of genetic interaction network structures and gene properties.” 2017. Web. 13 Dec 2019.

Vancouver:

Koch E. Computational analysis of genetic interaction network structures and gene properties. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/11299/190545.

Council of Science Editors:

Koch E. Computational analysis of genetic interaction network structures and gene properties. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/190545


Cornell University

6. Westbrook, Alexandra Michon. Characterization of RNA Genetic Regulators and Synthetic Networks .

Degree: 2018, Cornell University

 A central tenent of synthetic biology is the ability to predictably engineer complex patterns of gene expression. This fined tuned control allows us to reprogram… (more)

Subjects/Keywords: RNA; Biological control; Bioengineering; Biological Networks; synthetic biology

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APA (6th Edition):

Westbrook, A. M. (2018). Characterization of RNA Genetic Regulators and Synthetic Networks . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/59541

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):

Westbrook, Alexandra Michon. “Characterization of RNA Genetic Regulators and Synthetic Networks .” 2018. Thesis, Cornell University. Accessed December 13, 2019. http://hdl.handle.net/1813/59541.

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

MLA Handbook (7th Edition):

Westbrook, Alexandra Michon. “Characterization of RNA Genetic Regulators and Synthetic Networks .” 2018. Web. 13 Dec 2019.

Vancouver:

Westbrook AM. Characterization of RNA Genetic Regulators and Synthetic Networks . [Internet] [Thesis]. Cornell University; 2018. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/1813/59541.

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

Council of Science Editors:

Westbrook AM. Characterization of RNA Genetic Regulators and Synthetic Networks . [Thesis]. Cornell University; 2018. Available from: http://hdl.handle.net/1813/59541

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


Linnaeus University

7. Köstinger, Harald. ViNCent – Visualization of NetworkCentralities.

Degree: Physics and Mathematics, 2011, Linnaeus University

  In the area of information visualization social or biological networks are visualized ina way so that they can be explored easily and one can… (more)

Subjects/Keywords: centralities; network analysis; visualization; social networks; biological networks; graph drawing

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APA (6th Edition):

Köstinger, H. (2011). ViNCent – Visualization of NetworkCentralities. (Thesis). Linnaeus University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-10793

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):

Köstinger, Harald. “ViNCent – Visualization of NetworkCentralities.” 2011. Thesis, Linnaeus University. Accessed December 13, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-10793.

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

MLA Handbook (7th Edition):

Köstinger, Harald. “ViNCent – Visualization of NetworkCentralities.” 2011. Web. 13 Dec 2019.

Vancouver:

Köstinger H. ViNCent – Visualization of NetworkCentralities. [Internet] [Thesis]. Linnaeus University; 2011. [cited 2019 Dec 13]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-10793.

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

Council of Science Editors:

Köstinger H. ViNCent – Visualization of NetworkCentralities. [Thesis]. Linnaeus University; 2011. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-10793

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


University of Notre Dame

8. Soon-Hyung Yook. From the Topology to the Dynamics of Complex Networks</h1>.

Degree: PhD, Physics, 2004, University of Notre Dame

  Understanding the mechanisms governing the behavior of complex networks is a prerequisite for characterizing complex systems. Frequently, networks are modelled as unweighted graphs in… (more)

Subjects/Keywords: Random Networks; Biological Networks

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APA (6th Edition):

Yook, S. (2004). From the Topology to the Dynamics of Complex Networks</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/nv935140w9x

Chicago Manual of Style (16th Edition):

Yook, Soon-Hyung. “From the Topology to the Dynamics of Complex Networks</h1>.” 2004. Doctoral Dissertation, University of Notre Dame. Accessed December 13, 2019. https://curate.nd.edu/show/nv935140w9x.

MLA Handbook (7th Edition):

Yook, Soon-Hyung. “From the Topology to the Dynamics of Complex Networks</h1>.” 2004. Web. 13 Dec 2019.

Vancouver:

Yook S. From the Topology to the Dynamics of Complex Networks</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2004. [cited 2019 Dec 13]. Available from: https://curate.nd.edu/show/nv935140w9x.

Council of Science Editors:

Yook S. From the Topology to the Dynamics of Complex Networks</h1>. [Doctoral Dissertation]. University of Notre Dame; 2004. Available from: https://curate.nd.edu/show/nv935140w9x


University of California – Irvine

9. Patel Rajesh, Vishal. Large Scale Integration, Analysis, and Visualization of Biological Data.

Degree: Computer Science, 2014, University of California – Irvine

 Data from decades of life sciences research and literature is being curated and made available for searching and analysis. While considerable work has been done… (more)

Subjects/Keywords: Computer science; Bioinformatics; big data in biology; biological data analysis; biological networks; data integration

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APA (6th Edition):

Patel Rajesh, V. (2014). Large Scale Integration, Analysis, and Visualization of Biological Data. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/2wp2m4n5

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):

Patel Rajesh, Vishal. “Large Scale Integration, Analysis, and Visualization of Biological Data.” 2014. Thesis, University of California – Irvine. Accessed December 13, 2019. http://www.escholarship.org/uc/item/2wp2m4n5.

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

MLA Handbook (7th Edition):

Patel Rajesh, Vishal. “Large Scale Integration, Analysis, and Visualization of Biological Data.” 2014. Web. 13 Dec 2019.

Vancouver:

Patel Rajesh V. Large Scale Integration, Analysis, and Visualization of Biological Data. [Internet] [Thesis]. University of California – Irvine; 2014. [cited 2019 Dec 13]. Available from: http://www.escholarship.org/uc/item/2wp2m4n5.

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

Council of Science Editors:

Patel Rajesh V. Large Scale Integration, Analysis, and Visualization of Biological Data. [Thesis]. University of California – Irvine; 2014. Available from: http://www.escholarship.org/uc/item/2wp2m4n5

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


The Ohio State University

10. Uppalapati, Praneeth. Network Mining Approach to Cancer Biomarker Discovery.

Degree: MS, Computer Science and Engineering, 2010, The Ohio State University

  With the rapid development of high throughput gene expression profiling technology, molecule profiling has become a powerful tool to characterize disease subtypes and discover… (more)

Subjects/Keywords: Bioinformatics; Computer Science; Biomarker; Gene co-expression networks; Glioblastoma Multiforme; Network mining; Biological networks

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APA (6th Edition):

Uppalapati, P. (2010). Network Mining Approach to Cancer Biomarker Discovery. (Masters Thesis). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1275405677

Chicago Manual of Style (16th Edition):

Uppalapati, Praneeth. “Network Mining Approach to Cancer Biomarker Discovery.” 2010. Masters Thesis, The Ohio State University. Accessed December 13, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275405677.

MLA Handbook (7th Edition):

Uppalapati, Praneeth. “Network Mining Approach to Cancer Biomarker Discovery.” 2010. Web. 13 Dec 2019.

Vancouver:

Uppalapati P. Network Mining Approach to Cancer Biomarker Discovery. [Internet] [Masters thesis]. The Ohio State University; 2010. [cited 2019 Dec 13]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275405677.

Council of Science Editors:

Uppalapati P. Network Mining Approach to Cancer Biomarker Discovery. [Masters Thesis]. The Ohio State University; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275405677


Virginia Tech

11. Zhang, Bai. Modeling and Characterization of Dynamic Changes in Biological Systems from Multi-platform Genomic Data.

Degree: PhD, Electrical and Computer Engineering, 2011, Virginia Tech

Biological systems constantly evolve and adapt in response to changed environment and external stimuli at the molecular and genomic levels. Building statistical models that characterize… (more)

Subjects/Keywords: differential dependency networks; biological networks; echo state networks; DNA copy number changes; structural changes in graphical models

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APA (6th Edition):

Zhang, B. (2011). Modeling and Characterization of Dynamic Changes in Biological Systems from Multi-platform Genomic Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/29111

Chicago Manual of Style (16th Edition):

Zhang, Bai. “Modeling and Characterization of Dynamic Changes in Biological Systems from Multi-platform Genomic Data.” 2011. Doctoral Dissertation, Virginia Tech. Accessed December 13, 2019. http://hdl.handle.net/10919/29111.

MLA Handbook (7th Edition):

Zhang, Bai. “Modeling and Characterization of Dynamic Changes in Biological Systems from Multi-platform Genomic Data.” 2011. Web. 13 Dec 2019.

Vancouver:

Zhang B. Modeling and Characterization of Dynamic Changes in Biological Systems from Multi-platform Genomic Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/10919/29111.

Council of Science Editors:

Zhang B. Modeling and Characterization of Dynamic Changes in Biological Systems from Multi-platform Genomic Data. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/29111


The Ohio State University

12. Ucar, Duygu. Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery.

Degree: PhD, Computer Science and Engineering, 2009, The Ohio State University

 Many biological datasets can be effectively modeled as interaction networks where nodes represent biological entities of interest such as proteins, genes, or complexes and edges… (more)

Subjects/Keywords: Bioinformatics; Computer Science; Biological interaction networks; microarray; gene regulation

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APA (6th Edition):

Ucar, D. (2009). Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1250656196

Chicago Manual of Style (16th Edition):

Ucar, Duygu. “Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery.” 2009. Doctoral Dissertation, The Ohio State University. Accessed December 13, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250656196.

MLA Handbook (7th Edition):

Ucar, Duygu. “Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery.” 2009. Web. 13 Dec 2019.

Vancouver:

Ucar D. Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery. [Internet] [Doctoral dissertation]. The Ohio State University; 2009. [cited 2019 Dec 13]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1250656196.

Council of Science Editors:

Ucar D. Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery. [Doctoral Dissertation]. The Ohio State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1250656196


Penn State University

13. Saadatpour Moghaddam, Assieh. Dynamic Modeling of Biological and Physical Systems.

Degree: PhD, Mathematics, 2012, Penn State University

 Given the complexity and interactive nature of many biological and physical systems, constructing informative and coherent network models of these systems and subsequently developing efficient… (more)

Subjects/Keywords: Dynamic modeling; Biological networks; Boolean models; Piecewise linear models

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APA (6th Edition):

Saadatpour Moghaddam, A. (2012). Dynamic Modeling of Biological and Physical Systems. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/15348

Chicago Manual of Style (16th Edition):

Saadatpour Moghaddam, Assieh. “Dynamic Modeling of Biological and Physical Systems.” 2012. Doctoral Dissertation, Penn State University. Accessed December 13, 2019. https://etda.libraries.psu.edu/catalog/15348.

MLA Handbook (7th Edition):

Saadatpour Moghaddam, Assieh. “Dynamic Modeling of Biological and Physical Systems.” 2012. Web. 13 Dec 2019.

Vancouver:

Saadatpour Moghaddam A. Dynamic Modeling of Biological and Physical Systems. [Internet] [Doctoral dissertation]. Penn State University; 2012. [cited 2019 Dec 13]. Available from: https://etda.libraries.psu.edu/catalog/15348.

Council of Science Editors:

Saadatpour Moghaddam A. Dynamic Modeling of Biological and Physical Systems. [Doctoral Dissertation]. Penn State University; 2012. Available from: https://etda.libraries.psu.edu/catalog/15348

14. Yartseva Smidtas, Anastasia. Modélisation incrémentale des réseaux biologiques : Incremental modelling of biological networks.

Degree: Docteur es, Bioinformatique, 2007, Evry-Val d'Essonne

Le domaine scientifique de la Biologie des Systèmes étudie les interactions entre les composantes d'un système biologique afin d'en comprendre son fonctionnement global. Au cours… (more)

Subjects/Keywords: Réseaux biologiques; Biological networks

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APA (6th Edition):

Yartseva Smidtas, A. (2007). Modélisation incrémentale des réseaux biologiques : Incremental modelling of biological networks. (Doctoral Dissertation). Evry-Val d'Essonne. Retrieved from http://www.theses.fr/2007EVRY0025

Chicago Manual of Style (16th Edition):

Yartseva Smidtas, Anastasia. “Modélisation incrémentale des réseaux biologiques : Incremental modelling of biological networks.” 2007. Doctoral Dissertation, Evry-Val d'Essonne. Accessed December 13, 2019. http://www.theses.fr/2007EVRY0025.

MLA Handbook (7th Edition):

Yartseva Smidtas, Anastasia. “Modélisation incrémentale des réseaux biologiques : Incremental modelling of biological networks.” 2007. Web. 13 Dec 2019.

Vancouver:

Yartseva Smidtas A. Modélisation incrémentale des réseaux biologiques : Incremental modelling of biological networks. [Internet] [Doctoral dissertation]. Evry-Val d'Essonne; 2007. [cited 2019 Dec 13]. Available from: http://www.theses.fr/2007EVRY0025.

Council of Science Editors:

Yartseva Smidtas A. Modélisation incrémentale des réseaux biologiques : Incremental modelling of biological networks. [Doctoral Dissertation]. Evry-Val d'Essonne; 2007. Available from: http://www.theses.fr/2007EVRY0025

15. Δημητρακοπούλου, Κωνσταντίνα. Ανάλυση και μοντελοποίηση βιολογικών δικτύων με χρήση δεδομένων από μεγάλης κλίμακας τεχνικές της μοριακής βιολογίας.

Degree: 2013, University of Patras

 Στην εποχή της Συστημικής Ιατρικής, οι τεχνολογίες μαζικής καταγραφής της γονιδιακής και miRNA έκφρασης (π.χ. μικροσυστοιχίες, RNA-seq) αλλά και οι τεχνολογίες ανίχνευσης πρωτεϊνικών αλληλεπιδράσεων (π.χ.… (more)

Subjects/Keywords: Βιολογικά δίκτυα; Συστημική βιολογία; 570.285; Biological networks; Systems biology

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APA (6th Edition):

Δημητρακοπούλου, . (2013). Ανάλυση και μοντελοποίηση βιολογικών δικτύων με χρήση δεδομένων από μεγάλης κλίμακας τεχνικές της μοριακής βιολογίας. (Doctoral Dissertation). University of Patras. Retrieved from http://hdl.handle.net/10889/6965

Chicago Manual of Style (16th Edition):

Δημητρακοπούλου, Κωνσταντίνα. “Ανάλυση και μοντελοποίηση βιολογικών δικτύων με χρήση δεδομένων από μεγάλης κλίμακας τεχνικές της μοριακής βιολογίας.” 2013. Doctoral Dissertation, University of Patras. Accessed December 13, 2019. http://hdl.handle.net/10889/6965.

MLA Handbook (7th Edition):

Δημητρακοπούλου, Κωνσταντίνα. “Ανάλυση και μοντελοποίηση βιολογικών δικτύων με χρήση δεδομένων από μεγάλης κλίμακας τεχνικές της μοριακής βιολογίας.” 2013. Web. 13 Dec 2019.

Vancouver:

Δημητρακοπούλου . Ανάλυση και μοντελοποίηση βιολογικών δικτύων με χρήση δεδομένων από μεγάλης κλίμακας τεχνικές της μοριακής βιολογίας. [Internet] [Doctoral dissertation]. University of Patras; 2013. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/10889/6965.

Council of Science Editors:

Δημητρακοπούλου . Ανάλυση και μοντελοποίηση βιολογικών δικτύων με χρήση δεδομένων από μεγάλης κλίμακας τεχνικές της μοριακής βιολογίας. [Doctoral Dissertation]. University of Patras; 2013. Available from: http://hdl.handle.net/10889/6965


University of Illinois – Urbana-Champaign

16. Deviprasad Rao, Vikyath. Multiscale dynamics in honeybee societies.

Degree: PhD, Physics, 2016, University of Illinois – Urbana-Champaign

 In this dissertation, I examine the social organization of a model organism, the honeybee, at multiple scales. I begin in Part I at the microbial… (more)

Subjects/Keywords: complex systems; biological physics; honey bee; social networks; microbiome; metagenomics

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APA (6th Edition):

Deviprasad Rao, V. (2016). Multiscale dynamics in honeybee societies. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/95563

Chicago Manual of Style (16th Edition):

Deviprasad Rao, Vikyath. “Multiscale dynamics in honeybee societies.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed December 13, 2019. http://hdl.handle.net/2142/95563.

MLA Handbook (7th Edition):

Deviprasad Rao, Vikyath. “Multiscale dynamics in honeybee societies.” 2016. Web. 13 Dec 2019.

Vancouver:

Deviprasad Rao V. Multiscale dynamics in honeybee societies. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/2142/95563.

Council of Science Editors:

Deviprasad Rao V. Multiscale dynamics in honeybee societies. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/95563


Virginia Tech

17. Pokrzywa, Revonda Maria. Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2009, Virginia Tech

 One of the primary goals of systems biology is to understand the complex underlying network of biochemical interactions which allow an organism to respond to… (more)

Subjects/Keywords: Systems Biology; Metabolomics; Biological Networks

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APA (6th Edition):

Pokrzywa, R. M. (2009). Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/39938

Chicago Manual of Style (16th Edition):

Pokrzywa, Revonda Maria. “Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information.” 2009. Doctoral Dissertation, Virginia Tech. Accessed December 13, 2019. http://hdl.handle.net/10919/39938.

MLA Handbook (7th Edition):

Pokrzywa, Revonda Maria. “Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information.” 2009. Web. 13 Dec 2019.

Vancouver:

Pokrzywa RM. Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information. [Internet] [Doctoral dissertation]. Virginia Tech; 2009. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/10919/39938.

Council of Science Editors:

Pokrzywa RM. Systems Biology in an Imperfect World: Modeling Biological Systems with Incomplete Information. [Doctoral Dissertation]. Virginia Tech; 2009. Available from: http://hdl.handle.net/10919/39938

18. TRAN NGOC HIEU. Asymptotically unbiased and consistent estimation of motif counts in biological networks from noisy subnetwork data.

Degree: 2013, National University of Singapore

Subjects/Keywords: biological networks; motifs; subnetwork

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APA (6th Edition):

HIEU, T. N. (2013). Asymptotically unbiased and consistent estimation of motif counts in biological networks from noisy subnetwork data. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/47504

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):

HIEU, TRAN NGOC. “Asymptotically unbiased and consistent estimation of motif counts in biological networks from noisy subnetwork data.” 2013. Thesis, National University of Singapore. Accessed December 13, 2019. http://scholarbank.nus.edu.sg/handle/10635/47504.

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

MLA Handbook (7th Edition):

HIEU, TRAN NGOC. “Asymptotically unbiased and consistent estimation of motif counts in biological networks from noisy subnetwork data.” 2013. Web. 13 Dec 2019.

Vancouver:

HIEU TN. Asymptotically unbiased and consistent estimation of motif counts in biological networks from noisy subnetwork data. [Internet] [Thesis]. National University of Singapore; 2013. [cited 2019 Dec 13]. Available from: http://scholarbank.nus.edu.sg/handle/10635/47504.

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

Council of Science Editors:

HIEU TN. Asymptotically unbiased and consistent estimation of motif counts in biological networks from noisy subnetwork data. [Thesis]. National University of Singapore; 2013. Available from: http://scholarbank.nus.edu.sg/handle/10635/47504

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


University of Minnesota

19. Schaefer, Robert. Integrating Co-Expression Networks with GWAS to Detect Causal Genes For Agronomically Important Traits.

Degree: PhD, Biomedical Informatics and Computational Biology, 2015, University of Minnesota

 The recent availability of high-throughput technologies in agricultural species provides an opportunity to advance our understanding of complex, agronomically important traits. Genome wide association studies… (more)

Subjects/Keywords: arabidopsis; biological networks; Camoco; co-expression; computational biology; maize

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APA (6th Edition):

Schaefer, R. (2015). Integrating Co-Expression Networks with GWAS to Detect Causal Genes For Agronomically Important Traits. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/188892

Chicago Manual of Style (16th Edition):

Schaefer, Robert. “Integrating Co-Expression Networks with GWAS to Detect Causal Genes For Agronomically Important Traits.” 2015. Doctoral Dissertation, University of Minnesota. Accessed December 13, 2019. http://hdl.handle.net/11299/188892.

MLA Handbook (7th Edition):

Schaefer, Robert. “Integrating Co-Expression Networks with GWAS to Detect Causal Genes For Agronomically Important Traits.” 2015. Web. 13 Dec 2019.

Vancouver:

Schaefer R. Integrating Co-Expression Networks with GWAS to Detect Causal Genes For Agronomically Important Traits. [Internet] [Doctoral dissertation]. University of Minnesota; 2015. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/11299/188892.

Council of Science Editors:

Schaefer R. Integrating Co-Expression Networks with GWAS to Detect Causal Genes For Agronomically Important Traits. [Doctoral Dissertation]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/188892


Rice University

20. Peterson, Christine. Bayesian graphical models for biological network inference.

Degree: PhD, Engineering, 2013, Rice University

 In this work, we propose approaches for the inference of graphical models in the Bayesian framework. Graphical models, which use a network structure to represent… (more)

Subjects/Keywords: Statistics; Graphical models; Bayesian inference; Informative priors; Biological networks

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APA (6th Edition):

Peterson, C. (2013). Bayesian graphical models for biological network inference. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/77444

Chicago Manual of Style (16th Edition):

Peterson, Christine. “Bayesian graphical models for biological network inference.” 2013. Doctoral Dissertation, Rice University. Accessed December 13, 2019. http://hdl.handle.net/1911/77444.

MLA Handbook (7th Edition):

Peterson, Christine. “Bayesian graphical models for biological network inference.” 2013. Web. 13 Dec 2019.

Vancouver:

Peterson C. Bayesian graphical models for biological network inference. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/1911/77444.

Council of Science Editors:

Peterson C. Bayesian graphical models for biological network inference. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/77444


University of Michigan

21. Wang, Zhi. Evolutionary Systems Biology.

Degree: PhD, Ecology and Evolutionary Biology, 2010, University of Michigan

 By analyzing complex biological networks, I explore the nascent field of systems biology to address some of the most long-lasting and difficult questions in genetics… (more)

Subjects/Keywords: Systems Biology; Complex Biological Networks; Ecology and Evolutionary Biology; Science

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APA (6th Edition):

Wang, Z. (2010). Evolutionary Systems Biology. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/77868

Chicago Manual of Style (16th Edition):

Wang, Zhi. “Evolutionary Systems Biology.” 2010. Doctoral Dissertation, University of Michigan. Accessed December 13, 2019. http://hdl.handle.net/2027.42/77868.

MLA Handbook (7th Edition):

Wang, Zhi. “Evolutionary Systems Biology.” 2010. Web. 13 Dec 2019.

Vancouver:

Wang Z. Evolutionary Systems Biology. [Internet] [Doctoral dissertation]. University of Michigan; 2010. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/2027.42/77868.

Council of Science Editors:

Wang Z. Evolutionary Systems Biology. [Doctoral Dissertation]. University of Michigan; 2010. Available from: http://hdl.handle.net/2027.42/77868


Virginia Tech

22. Black, Jacob A. Neural Networks For Phase Demodulation In Optical Interferometry.

Degree: MS, Electrical Engineering, 2019, Virginia Tech

 Neural Networks (NNs) (or 'deep' neural networks (DNNs)) have found great success in many applications across all fields of engineering, and in particular have found… (more)

Subjects/Keywords: Phase imaging; Neural Networks; Machine Learning; Biological Imaging

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APA (6th Edition):

Black, J. A. (2019). Neural Networks For Phase Demodulation In Optical Interferometry. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/93263

Chicago Manual of Style (16th Edition):

Black, Jacob A. “Neural Networks For Phase Demodulation In Optical Interferometry.” 2019. Masters Thesis, Virginia Tech. Accessed December 13, 2019. http://hdl.handle.net/10919/93263.

MLA Handbook (7th Edition):

Black, Jacob A. “Neural Networks For Phase Demodulation In Optical Interferometry.” 2019. Web. 13 Dec 2019.

Vancouver:

Black JA. Neural Networks For Phase Demodulation In Optical Interferometry. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2019 Dec 13]. Available from: http://hdl.handle.net/10919/93263.

Council of Science Editors:

Black JA. Neural Networks For Phase Demodulation In Optical Interferometry. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/93263

23. Pirayre, Aurélie. Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images : Reconstruction and clustering with graph optimization and priors on gene networks and images.

Degree: Docteur es, Signal, Image, Automatique, 2017, Université Paris-Est

 Dans de nombreuses applications telles que la médecine, l'environnement ou les biotechnologies par exemple, la découverte de nouveau processus de régulations de gènes permet une… (more)

Subjects/Keywords: Réseaux biologiques; Graphes; A priori; Modèles biologiques; Optimisation; Biological networks; Graphs; A priori; Biological models; Optimization

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APA (6th Edition):

Pirayre, A. (2017). Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images : Reconstruction and clustering with graph optimization and priors on gene networks and images. (Doctoral Dissertation). Université Paris-Est. Retrieved from http://www.theses.fr/2017PESC1170

Chicago Manual of Style (16th Edition):

Pirayre, Aurélie. “Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images : Reconstruction and clustering with graph optimization and priors on gene networks and images.” 2017. Doctoral Dissertation, Université Paris-Est. Accessed December 13, 2019. http://www.theses.fr/2017PESC1170.

MLA Handbook (7th Edition):

Pirayre, Aurélie. “Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images : Reconstruction and clustering with graph optimization and priors on gene networks and images.” 2017. Web. 13 Dec 2019.

Vancouver:

Pirayre A. Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images : Reconstruction and clustering with graph optimization and priors on gene networks and images. [Internet] [Doctoral dissertation]. Université Paris-Est; 2017. [cited 2019 Dec 13]. Available from: http://www.theses.fr/2017PESC1170.

Council of Science Editors:

Pirayre A. Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images : Reconstruction and clustering with graph optimization and priors on gene networks and images. [Doctoral Dissertation]. Université Paris-Est; 2017. Available from: http://www.theses.fr/2017PESC1170


Penn State University

24. Madireddy, Manini. DATA MINING AND NETWORK MINING APPROACH FOR SIGNIFICANT PROTEIN IDENTIFICATION IN GASTRIC BYPASS SURGERY.

Degree: MS, Industrial Engineering, 2009, Penn State University

 In this research project our focus was to understand the underlying biological causes, identify the significant proteins and the most probable drug targets of diabetes.… (more)

Subjects/Keywords: Mass Spectrometry; Diabetes; Gene Filtering; Complex Networks; Systems Biology; Biological Networks; Protein Interaction Network; Bariatric Surgery

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APA (6th Edition):

Madireddy, M. (2009). DATA MINING AND NETWORK MINING APPROACH FOR SIGNIFICANT PROTEIN IDENTIFICATION IN GASTRIC BYPASS SURGERY. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9102

Chicago Manual of Style (16th Edition):

Madireddy, Manini. “DATA MINING AND NETWORK MINING APPROACH FOR SIGNIFICANT PROTEIN IDENTIFICATION IN GASTRIC BYPASS SURGERY.” 2009. Masters Thesis, Penn State University. Accessed December 13, 2019. https://etda.libraries.psu.edu/catalog/9102.

MLA Handbook (7th Edition):

Madireddy, Manini. “DATA MINING AND NETWORK MINING APPROACH FOR SIGNIFICANT PROTEIN IDENTIFICATION IN GASTRIC BYPASS SURGERY.” 2009. Web. 13 Dec 2019.

Vancouver:

Madireddy M. DATA MINING AND NETWORK MINING APPROACH FOR SIGNIFICANT PROTEIN IDENTIFICATION IN GASTRIC BYPASS SURGERY. [Internet] [Masters thesis]. Penn State University; 2009. [cited 2019 Dec 13]. Available from: https://etda.libraries.psu.edu/catalog/9102.

Council of Science Editors:

Madireddy M. DATA MINING AND NETWORK MINING APPROACH FOR SIGNIFICANT PROTEIN IDENTIFICATION IN GASTRIC BYPASS SURGERY. [Masters Thesis]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9102

25. Schuman, Catherine Dorothy. Neuroscience-Inspired Dynamic Architectures.

Degree: 2015, University of Tennessee – Knoxville

Biological brains are some of the most powerful computational devices on Earth. Computer scientists have long drawn inspiration from neuroscience to produce computational tools. This… (more)

Subjects/Keywords: machine learning; neural networks; discrete event simulation; biological networks; optimization algorithms; Artificial Intelligence and Robotics; Theory and Algorithms

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APA (6th Edition):

Schuman, C. D. (2015). Neuroscience-Inspired Dynamic Architectures. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/3361

Chicago Manual of Style (16th Edition):

Schuman, Catherine Dorothy. “Neuroscience-Inspired Dynamic Architectures.” 2015. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed December 13, 2019. https://trace.tennessee.edu/utk_graddiss/3361.

MLA Handbook (7th Edition):

Schuman, Catherine Dorothy. “Neuroscience-Inspired Dynamic Architectures.” 2015. Web. 13 Dec 2019.

Vancouver:

Schuman CD. Neuroscience-Inspired Dynamic Architectures. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2015. [cited 2019 Dec 13]. Available from: https://trace.tennessee.edu/utk_graddiss/3361.

Council of Science Editors:

Schuman CD. Neuroscience-Inspired Dynamic Architectures. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2015. Available from: https://trace.tennessee.edu/utk_graddiss/3361


Linköping University

26. Åkesson, Julia. Robust Community Predictions of Hubs in Gene Regulatory Networks.

Degree: Bioinformatics, 2018, Linköping University

  Many diseases, such as cardiovascular diseases, cancer and diabetes, originate from several malfunctions in biological systems. The human body is regulated by a wide… (more)

Subjects/Keywords: Biological systems; Biological networks; Network inference; Gene regulatory networks; Hubs; Master regulators; Community predictions; Bioinformatics; Bioinformatics and Systems Biology; Bioinformatik och systembiologi

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APA (6th Edition):

Åkesson, J. (2018). Robust Community Predictions of Hubs in Gene Regulatory Networks. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153200

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):

Åkesson, Julia. “Robust Community Predictions of Hubs in Gene Regulatory Networks.” 2018. Thesis, Linköping University. Accessed December 13, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153200.

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

MLA Handbook (7th Edition):

Åkesson, Julia. “Robust Community Predictions of Hubs in Gene Regulatory Networks.” 2018. Web. 13 Dec 2019.

Vancouver:

Åkesson J. Robust Community Predictions of Hubs in Gene Regulatory Networks. [Internet] [Thesis]. Linköping University; 2018. [cited 2019 Dec 13]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153200.

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

Council of Science Editors:

Åkesson J. Robust Community Predictions of Hubs in Gene Regulatory Networks. [Thesis]. Linköping University; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153200

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


Anna University

27. Nirmala Devi, M. VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -.

Degree: Information and Communication Engineering, 2014, Anna University

A Biological Neural Network BNN forms the Central Nervous newlineSystem which has highly interconnected neurons to co ordinate all the newlinefunctions like reading and thinking… (more)

Subjects/Keywords: Artificial Neural Networks; Biological Neural Network; Central Nervous System; Very Large Scale Integration

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APA (6th Edition):

Nirmala Devi, M. (2014). VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/26986

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):

Nirmala Devi, M. “VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -.” 2014. Thesis, Anna University. Accessed December 13, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/26986.

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

MLA Handbook (7th Edition):

Nirmala Devi, M. “VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -.” 2014. Web. 13 Dec 2019.

Vancouver:

Nirmala Devi M. VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Dec 13]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26986.

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

Council of Science Editors:

Nirmala Devi M. VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26986

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


Penn State University

28. Sun, Zhongyao. Analysis and Logical Modeling of Biological Signaling Transduction Networks.

Degree: PhD, Physics, 2015, Penn State University

 The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science,… (more)

Subjects/Keywords: network science; biological networks; discrete dynamics; Boolean network; system biology; network modeling; signal transduction

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

APA (6th Edition):

Sun, Z. (2015). Analysis and Logical Modeling of Biological Signaling Transduction Networks. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/25268

Chicago Manual of Style (16th Edition):

Sun, Zhongyao. “Analysis and Logical Modeling of Biological Signaling Transduction Networks.” 2015. Doctoral Dissertation, Penn State University. Accessed December 13, 2019. https://etda.libraries.psu.edu/catalog/25268.

MLA Handbook (7th Edition):

Sun, Zhongyao. “Analysis and Logical Modeling of Biological Signaling Transduction Networks.” 2015. Web. 13 Dec 2019.

Vancouver:

Sun Z. Analysis and Logical Modeling of Biological Signaling Transduction Networks. [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2019 Dec 13]. Available from: https://etda.libraries.psu.edu/catalog/25268.

Council of Science Editors:

Sun Z. Analysis and Logical Modeling of Biological Signaling Transduction Networks. [Doctoral Dissertation]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/25268


University of California – San Diego

29. Ellen, Jeffrey Scott. Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata.

Degree: Computer Science and Engineering, 2018, University of California – San Diego

 For the past few years, Convolutional Neural Networks have had tremendous impact not only within the field of Computer Science but by 2018 their rapid… (more)

Subjects/Keywords: Artificial intelligence; Biological oceanography; convolutional neural networks; image processing; machine learning; zooplankton

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APA (6th Edition):

Ellen, J. S. (2018). Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/8f18p61p

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):

Ellen, Jeffrey Scott. “Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata.” 2018. Thesis, University of California – San Diego. Accessed December 13, 2019. http://www.escholarship.org/uc/item/8f18p61p.

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

MLA Handbook (7th Edition):

Ellen, Jeffrey Scott. “Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata.” 2018. Web. 13 Dec 2019.

Vancouver:

Ellen JS. Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata. [Internet] [Thesis]. University of California – San Diego; 2018. [cited 2019 Dec 13]. Available from: http://www.escholarship.org/uc/item/8f18p61p.

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

Council of Science Editors:

Ellen JS. Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata. [Thesis]. University of California – San Diego; 2018. Available from: http://www.escholarship.org/uc/item/8f18p61p

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

30. Fu, Yao. Understand biological regulatory systems using computational models: Reconstruction, Analysis and Integration.

Degree: 2013, Iowa State University

Biological regulatory system is complex and involves many types of interactions, including transcriptional regulations, protein interactions, metabolic reactions and etc., to ensure the regulations of… (more)

Subjects/Keywords: Biological Regulation; Gene Regulation; Regulatory Networks; Regulatory System; Transcription Factor; Bioinformatics; Systems Biology

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

APA (6th Edition):

Fu, Y. (2013). Understand biological regulatory systems using computational models: Reconstruction, Analysis and Integration. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/13435

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):

Fu, Yao. “Understand biological regulatory systems using computational models: Reconstruction, Analysis and Integration.” 2013. Thesis, Iowa State University. Accessed December 13, 2019. https://lib.dr.iastate.edu/etd/13435.

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

MLA Handbook (7th Edition):

Fu, Yao. “Understand biological regulatory systems using computational models: Reconstruction, Analysis and Integration.” 2013. Web. 13 Dec 2019.

Vancouver:

Fu Y. Understand biological regulatory systems using computational models: Reconstruction, Analysis and Integration. [Internet] [Thesis]. Iowa State University; 2013. [cited 2019 Dec 13]. Available from: https://lib.dr.iastate.edu/etd/13435.

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

Council of Science Editors:

Fu Y. Understand biological regulatory systems using computational models: Reconstruction, Analysis and Integration. [Thesis]. Iowa State University; 2013. Available from: https://lib.dr.iastate.edu/etd/13435

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

[1] [2] [3] [4] [5]

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