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You searched for subject:(Gene regulation network). Showing records 1 – 30 of 34 total matches.

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Virginia Tech

1. Kadelka, Claus Thomas. Robustness Analysis of Gene Regulatory Networks.

Degree: PhD, Mathematics, 2015, Virginia Tech

 Cells generally manage to maintain stable phenotypes in the face of widely varying environmental conditions. This fact is particularly surprising since the key step of… (more)

Subjects/Keywords: Boolean network; gene regulation; stability

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APA (6th Edition):

Kadelka, C. T. (2015). Robustness Analysis of Gene Regulatory Networks. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73302

Chicago Manual of Style (16th Edition):

Kadelka, Claus Thomas. “Robustness Analysis of Gene Regulatory Networks.” 2015. Doctoral Dissertation, Virginia Tech. Accessed March 28, 2020. http://hdl.handle.net/10919/73302.

MLA Handbook (7th Edition):

Kadelka, Claus Thomas. “Robustness Analysis of Gene Regulatory Networks.” 2015. Web. 28 Mar 2020.

Vancouver:

Kadelka CT. Robustness Analysis of Gene Regulatory Networks. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10919/73302.

Council of Science Editors:

Kadelka CT. Robustness Analysis of Gene Regulatory Networks. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/73302


University of Cincinnati

2. GHANEM, AMER. A Modular Gene Regulation Network Model of Artificial Ontogenesis.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

 A fundamental issue in evolution is the balance between variation and stability. Change isnecessary for the evolution of fitter forms, but it cannot come at… (more)

Subjects/Keywords: Computer Science; Artificial ontogenesis; Modular Gene regulation; Gene regulation network

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APA (6th Edition):

GHANEM, A. (2008). A Modular Gene Regulation Network Model of Artificial Ontogenesis. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1204580560

Chicago Manual of Style (16th Edition):

GHANEM, AMER. “A Modular Gene Regulation Network Model of Artificial Ontogenesis.” 2008. Masters Thesis, University of Cincinnati. Accessed March 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1204580560.

MLA Handbook (7th Edition):

GHANEM, AMER. “A Modular Gene Regulation Network Model of Artificial Ontogenesis.” 2008. Web. 28 Mar 2020.

Vancouver:

GHANEM A. A Modular Gene Regulation Network Model of Artificial Ontogenesis. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2020 Mar 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1204580560.

Council of Science Editors:

GHANEM A. A Modular Gene Regulation Network Model of Artificial Ontogenesis. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1204580560


University of Cambridge

3. Olan, Ioana. Regulatory Landscapes Associated With Changes In Nuclear Architecture.

Degree: PhD, 2019, University of Cambridge

Gene regulation is essential for establishing a cell’s identity and relation with surrounding cells. A major role in modulating gene regulation is played by the… (more)

Subjects/Keywords: senescence; chromatin; network; gene regulation; community detection

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APA (6th Edition):

Olan, I. (2019). Regulatory Landscapes Associated With Changes In Nuclear Architecture. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/293014

Chicago Manual of Style (16th Edition):

Olan, Ioana. “Regulatory Landscapes Associated With Changes In Nuclear Architecture.” 2019. Doctoral Dissertation, University of Cambridge. Accessed March 28, 2020. https://www.repository.cam.ac.uk/handle/1810/293014.

MLA Handbook (7th Edition):

Olan, Ioana. “Regulatory Landscapes Associated With Changes In Nuclear Architecture.” 2019. Web. 28 Mar 2020.

Vancouver:

Olan I. Regulatory Landscapes Associated With Changes In Nuclear Architecture. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2020 Mar 28]. Available from: https://www.repository.cam.ac.uk/handle/1810/293014.

Council of Science Editors:

Olan I. Regulatory Landscapes Associated With Changes In Nuclear Architecture. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/293014


University of Dayton

4. Camino, Eric M. A Mechanistic Analysis of Gene Regulation and its Evolution in a Drosophila Model.

Degree: PhD, Biology, 2016, University of Dayton

 The body plans and adorning characteristics of animals have evolved impressively diverse morphologies. These body plans and characteristics are the products of networks of genes… (more)

Subjects/Keywords: Biology; cis-regulatory element; gene regulatory network; gene regulation; GRN evolution

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APA (6th Edition):

Camino, E. M. (2016). A Mechanistic Analysis of Gene Regulation and its Evolution in a Drosophila Model. (Doctoral Dissertation). University of Dayton. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461242188

Chicago Manual of Style (16th Edition):

Camino, Eric M. “A Mechanistic Analysis of Gene Regulation and its Evolution in a Drosophila Model.” 2016. Doctoral Dissertation, University of Dayton. Accessed March 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461242188.

MLA Handbook (7th Edition):

Camino, Eric M. “A Mechanistic Analysis of Gene Regulation and its Evolution in a Drosophila Model.” 2016. Web. 28 Mar 2020.

Vancouver:

Camino EM. A Mechanistic Analysis of Gene Regulation and its Evolution in a Drosophila Model. [Internet] [Doctoral dissertation]. University of Dayton; 2016. [cited 2020 Mar 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461242188.

Council of Science Editors:

Camino EM. A Mechanistic Analysis of Gene Regulation and its Evolution in a Drosophila Model. [Doctoral Dissertation]. University of Dayton; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461242188


Virginia Tech

5. Altarawy, Doaa Abdelsalam Ahmed Mohamed. DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks.

Degree: PhD, Computer Science, 2017, Virginia Tech

 With the abundance of biological data, computational prediction of gene regulatory networks (GRNs) from gene expression data has become more feasible. Although incorporating other prior… (more)

Subjects/Keywords: Gene regulation; prior knowledge; gene regulatory network inference; visualization; machine learning

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APA (6th Edition):

Altarawy, D. A. A. M. (2017). DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/85504

Chicago Manual of Style (16th Edition):

Altarawy, Doaa Abdelsalam Ahmed Mohamed. “DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks.” 2017. Doctoral Dissertation, Virginia Tech. Accessed March 28, 2020. http://hdl.handle.net/10919/85504.

MLA Handbook (7th Edition):

Altarawy, Doaa Abdelsalam Ahmed Mohamed. “DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks.” 2017. Web. 28 Mar 2020.

Vancouver:

Altarawy DAAM. DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10919/85504.

Council of Science Editors:

Altarawy DAAM. DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/85504


University of Illinois – Urbana-Champaign

6. Chen, Chieh-Chun. Analysis of combinatorial gene regulation with thermodynamic models.

Degree: MS, 0408, 2010, University of Illinois – Urbana-Champaign

 Transcriptional control is a key regulatory mechanism for cells to direct their destinies. A large number of transcription factors (TFs) could simultaneously bind to a… (more)

Subjects/Keywords: Gene Regulation; Gene Regulatory Network

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APA (6th Edition):

Chen, C. (2010). Analysis of combinatorial gene regulation with thermodynamic models. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/14656

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, Chieh-Chun. “Analysis of combinatorial gene regulation with thermodynamic models.” 2010. Thesis, University of Illinois – Urbana-Champaign. Accessed March 28, 2020. http://hdl.handle.net/2142/14656.

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

MLA Handbook (7th Edition):

Chen, Chieh-Chun. “Analysis of combinatorial gene regulation with thermodynamic models.” 2010. Web. 28 Mar 2020.

Vancouver:

Chen C. Analysis of combinatorial gene regulation with thermodynamic models. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2010. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/2142/14656.

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

Council of Science Editors:

Chen C. Analysis of combinatorial gene regulation with thermodynamic models. [Thesis]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/14656

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


New Jersey Institute of Technology

7. Somoza, Maria E. Gene network understanding and analysis.

Degree: MSin Bioinformatics - (M.S.), Computer Science, 2016, New Jersey Institute of Technology

Gene regulatory network (GRN) is a collection of regulators that interact with each other in the cell to govern the gene expression levels of… (more)

Subjects/Keywords: Gene regulatory network; Transcriptional gene regulation; Gene co-expression networks; Correlation networks; Bioinformatics; Computer Sciences

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APA (6th Edition):

Somoza, M. E. (2016). Gene network understanding and analysis. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/279

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):

Somoza, Maria E. “Gene network understanding and analysis.” 2016. Thesis, New Jersey Institute of Technology. Accessed March 28, 2020. https://digitalcommons.njit.edu/theses/279.

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

MLA Handbook (7th Edition):

Somoza, Maria E. “Gene network understanding and analysis.” 2016. Web. 28 Mar 2020.

Vancouver:

Somoza ME. Gene network understanding and analysis. [Internet] [Thesis]. New Jersey Institute of Technology; 2016. [cited 2020 Mar 28]. Available from: https://digitalcommons.njit.edu/theses/279.

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

Council of Science Editors:

Somoza ME. Gene network understanding and analysis. [Thesis]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/theses/279

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


Universiteit Utrecht

8. Kraal, L. Transcriptional Regulatory Networks in Saccharomyces cerevisiae.

Degree: 2009, Universiteit Utrecht

 One of the main goals of systems biology is reverse engineering network structures from experimental data. Using quantitative networks measures, biological processes can be characterized… (more)

Subjects/Keywords: Geneeskunde; network; transcription; Saccharomyces cerevisiae; robustness; network biology; systems biology; gene regulation; transcriptional regulatory network

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APA (6th Edition):

Kraal, L. (2009). Transcriptional Regulatory Networks in Saccharomyces cerevisiae. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/35359

Chicago Manual of Style (16th Edition):

Kraal, L. “Transcriptional Regulatory Networks in Saccharomyces cerevisiae.” 2009. Masters Thesis, Universiteit Utrecht. Accessed March 28, 2020. http://dspace.library.uu.nl:8080/handle/1874/35359.

MLA Handbook (7th Edition):

Kraal, L. “Transcriptional Regulatory Networks in Saccharomyces cerevisiae.” 2009. Web. 28 Mar 2020.

Vancouver:

Kraal L. Transcriptional Regulatory Networks in Saccharomyces cerevisiae. [Internet] [Masters thesis]. Universiteit Utrecht; 2009. [cited 2020 Mar 28]. Available from: http://dspace.library.uu.nl:8080/handle/1874/35359.

Council of Science Editors:

Kraal L. Transcriptional Regulatory Networks in Saccharomyces cerevisiae. [Masters Thesis]. Universiteit Utrecht; 2009. Available from: http://dspace.library.uu.nl:8080/handle/1874/35359


Queensland University of Technology

9. Chua, Xin-Yi. Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach.

Degree: 2012, Queensland University of Technology

 Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become… (more)

Subjects/Keywords: transcriptional regulatory interactions; bacteria; genomics approach; gene regulation; transcriptional regulatory network

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APA (6th Edition):

Chua, X. (2012). Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/55249/

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):

Chua, Xin-Yi. “Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach.” 2012. Thesis, Queensland University of Technology. Accessed March 28, 2020. https://eprints.qut.edu.au/55249/.

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

MLA Handbook (7th Edition):

Chua, Xin-Yi. “Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach.” 2012. Web. 28 Mar 2020.

Vancouver:

Chua X. Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach. [Internet] [Thesis]. Queensland University of Technology; 2012. [cited 2020 Mar 28]. Available from: https://eprints.qut.edu.au/55249/.

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

Council of Science Editors:

Chua X. Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach. [Thesis]. Queensland University of Technology; 2012. Available from: https://eprints.qut.edu.au/55249/

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


Universitat Pompeu Fabra

10. Lloréns Rico, Verónica, 1989-. Integrative understanding of transcription in a minimal cell model.

Degree: Departament de Ciències Experimentals i de la Salut, 2016, Universitat Pompeu Fabra

 Uno de los mayores retos de la biología es entender cómo células u organismos completos se comportan tanto en homeostasis como en respuesta a perturbaciones.… (more)

Subjects/Keywords: Transcription; Regulation; Whole-cell mode; Antisense RNAs; Gene regulatory network; 576

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APA (6th Edition):

Lloréns Rico, Verónica, 1. (2016). Integrative understanding of transcription in a minimal cell model. (Thesis). Universitat Pompeu Fabra. Retrieved from http://hdl.handle.net/10803/459003

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):

Lloréns Rico, Verónica, 1989-. “Integrative understanding of transcription in a minimal cell model.” 2016. Thesis, Universitat Pompeu Fabra. Accessed March 28, 2020. http://hdl.handle.net/10803/459003.

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

MLA Handbook (7th Edition):

Lloréns Rico, Verónica, 1989-. “Integrative understanding of transcription in a minimal cell model.” 2016. Web. 28 Mar 2020.

Vancouver:

Lloréns Rico, Verónica 1. Integrative understanding of transcription in a minimal cell model. [Internet] [Thesis]. Universitat Pompeu Fabra; 2016. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10803/459003.

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

Council of Science Editors:

Lloréns Rico, Verónica 1. Integrative understanding of transcription in a minimal cell model. [Thesis]. Universitat Pompeu Fabra; 2016. Available from: http://hdl.handle.net/10803/459003

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


University of California – San Francisco

11. Biddle-Snead, Charles. Statistical Characterization of Biochemical Network Models.

Degree: Biophysics, 2013, University of California – San Francisco

 Complex systems of numerous interacting biomolecules dictate cellular behavior. To better understand how these systems operate in aggregate, computational models of these systems may be… (more)

Subjects/Keywords: Biology; Cell Signaling; Gene Regulation; Network Modeling; Parameter Uncertainty; Systems Biology

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APA (6th Edition):

Biddle-Snead, C. (2013). Statistical Characterization of Biochemical Network Models. (Thesis). University of California – San Francisco. Retrieved from http://www.escholarship.org/uc/item/1v47h0w2

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):

Biddle-Snead, Charles. “Statistical Characterization of Biochemical Network Models.” 2013. Thesis, University of California – San Francisco. Accessed March 28, 2020. http://www.escholarship.org/uc/item/1v47h0w2.

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

MLA Handbook (7th Edition):

Biddle-Snead, Charles. “Statistical Characterization of Biochemical Network Models.” 2013. Web. 28 Mar 2020.

Vancouver:

Biddle-Snead C. Statistical Characterization of Biochemical Network Models. [Internet] [Thesis]. University of California – San Francisco; 2013. [cited 2020 Mar 28]. Available from: http://www.escholarship.org/uc/item/1v47h0w2.

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

Council of Science Editors:

Biddle-Snead C. Statistical Characterization of Biochemical Network Models. [Thesis]. University of California – San Francisco; 2013. Available from: http://www.escholarship.org/uc/item/1v47h0w2

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


Princeton University

12. Smith, Eric Michael. Scaling and regulation of gene expression in the developing fly embryo .

Degree: PhD, 2015, Princeton University

 The early embryo of the fruit fly Drosophila melanogaster has long been a model system in which to investigate questions of how cells acquire information… (more)

Subjects/Keywords: Bicoid; Drosophila; Hunchback; Morphogenesis; Patterning gene network; Transcriptional regulation

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APA (6th Edition):

Smith, E. M. (2015). Scaling and regulation of gene expression in the developing fly embryo . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp015138jh19k

Chicago Manual of Style (16th Edition):

Smith, Eric Michael. “Scaling and regulation of gene expression in the developing fly embryo .” 2015. Doctoral Dissertation, Princeton University. Accessed March 28, 2020. http://arks.princeton.edu/ark:/88435/dsp015138jh19k.

MLA Handbook (7th Edition):

Smith, Eric Michael. “Scaling and regulation of gene expression in the developing fly embryo .” 2015. Web. 28 Mar 2020.

Vancouver:

Smith EM. Scaling and regulation of gene expression in the developing fly embryo . [Internet] [Doctoral dissertation]. Princeton University; 2015. [cited 2020 Mar 28]. Available from: http://arks.princeton.edu/ark:/88435/dsp015138jh19k.

Council of Science Editors:

Smith EM. Scaling and regulation of gene expression in the developing fly embryo . [Doctoral Dissertation]. Princeton University; 2015. Available from: http://arks.princeton.edu/ark:/88435/dsp015138jh19k


University of Toronto

13. Li, Yue. Computational Methods of Inferring Context-specific MicroRNA Regulatory Networks.

Degree: PhD, 2015, University of Toronto

 MicroRNA (miRNA) is a class of small endogenous non-coding RNA species, which regulate gene expression post-transcriptionally by forming imperfect basepair with the target sites primarily… (more)

Subjects/Keywords: Cancer; Gene regulation; Machine Learning; MicroRNA; Network analysis; Probabilistic models; 0715

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

APA (6th Edition):

Li, Y. (2015). Computational Methods of Inferring Context-specific MicroRNA Regulatory Networks. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/69406

Chicago Manual of Style (16th Edition):

Li, Yue. “Computational Methods of Inferring Context-specific MicroRNA Regulatory Networks.” 2015. Doctoral Dissertation, University of Toronto. Accessed March 28, 2020. http://hdl.handle.net/1807/69406.

MLA Handbook (7th Edition):

Li, Yue. “Computational Methods of Inferring Context-specific MicroRNA Regulatory Networks.” 2015. Web. 28 Mar 2020.

Vancouver:

Li Y. Computational Methods of Inferring Context-specific MicroRNA Regulatory Networks. [Internet] [Doctoral dissertation]. University of Toronto; 2015. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1807/69406.

Council of Science Editors:

Li Y. Computational Methods of Inferring Context-specific MicroRNA Regulatory Networks. [Doctoral Dissertation]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/69406


University of Illinois – Chicago

14. Carson, Matthew B. Investigation of Gene Regulation and its Application to Disease Using Machine Learning and Network Models.

Degree: 2013, University of Illinois – Chicago

Gene regulation is one of the most important functions in the cell. Changes in the way a gene is regulated can either increase the versatility… (more)

Subjects/Keywords: machine learning; gene regulation; transcription factor network; alternating decision tree; disease network

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APA (6th Edition):

Carson, M. B. (2013). Investigation of Gene Regulation and its Application to Disease Using Machine Learning and Network Models. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/10061

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):

Carson, Matthew B. “Investigation of Gene Regulation and its Application to Disease Using Machine Learning and Network Models.” 2013. Thesis, University of Illinois – Chicago. Accessed March 28, 2020. http://hdl.handle.net/10027/10061.

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

MLA Handbook (7th Edition):

Carson, Matthew B. “Investigation of Gene Regulation and its Application to Disease Using Machine Learning and Network Models.” 2013. Web. 28 Mar 2020.

Vancouver:

Carson MB. Investigation of Gene Regulation and its Application to Disease Using Machine Learning and Network Models. [Internet] [Thesis]. University of Illinois – Chicago; 2013. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10027/10061.

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

Council of Science Editors:

Carson MB. Investigation of Gene Regulation and its Application to Disease Using Machine Learning and Network Models. [Thesis]. University of Illinois – Chicago; 2013. Available from: http://hdl.handle.net/10027/10061

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


Duke University

15. Cheng, Xianrui. Mechanistic Modeling and Experiments on Cell Fate Specification in the Sea Urchin Embryo .

Degree: 2012, Duke University

  During embryogenesis, a single zygote gives rise to a multicellular embryo with distinct spatial territories marked by differential gene expression. How is this patterning… (more)

Subjects/Keywords: Bioinformatics; Developmental biology; Physics; Boolean model; Dynamics; Embryonic development; Gene regulation; Network; Pattern formation

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APA (6th Edition):

Cheng, X. (2012). Mechanistic Modeling and Experiments on Cell Fate Specification in the Sea Urchin Embryo . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/6119

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

Chicago Manual of Style (16th Edition):

Cheng, Xianrui. “Mechanistic Modeling and Experiments on Cell Fate Specification in the Sea Urchin Embryo .” 2012. Thesis, Duke University. Accessed March 28, 2020. http://hdl.handle.net/10161/6119.

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

MLA Handbook (7th Edition):

Cheng, Xianrui. “Mechanistic Modeling and Experiments on Cell Fate Specification in the Sea Urchin Embryo .” 2012. Web. 28 Mar 2020.

Vancouver:

Cheng X. Mechanistic Modeling and Experiments on Cell Fate Specification in the Sea Urchin Embryo . [Internet] [Thesis]. Duke University; 2012. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10161/6119.

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

Council of Science Editors:

Cheng X. Mechanistic Modeling and Experiments on Cell Fate Specification in the Sea Urchin Embryo . [Thesis]. Duke University; 2012. Available from: http://hdl.handle.net/10161/6119

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

16. Aravena Duarte, Andrés Octavio. Probabilistic and constraint based modelling to determine regulation events from heterogeneous biological data : Modélisation probabiliste ou à base de contraintes pour déterminer des régulations à partir de données biologiques hétérogènes.

Degree: Docteur es, Informatique, 2013, Rennes 1; Universidad de Chile

Cette thèse propose une méthode pour construire des réseaux de régulations causales réalistes, qui a un taux de faux positifs inférieur aux méthodes traditionnelles. Cette… (more)

Subjects/Keywords: Bioinformatique; Biologie des systèmes; Réseau de régulations génétiques; Modélisation; Reconstruction de réseau; Bioinformatics; Systems biology; Gene regulation network; Modelling; Network reconstruction

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

APA (6th Edition):

Aravena Duarte, A. O. (2013). Probabilistic and constraint based modelling to determine regulation events from heterogeneous biological data : Modélisation probabiliste ou à base de contraintes pour déterminer des régulations à partir de données biologiques hétérogènes. (Doctoral Dissertation). Rennes 1; Universidad de Chile. Retrieved from http://www.theses.fr/2013REN1S151

Chicago Manual of Style (16th Edition):

Aravena Duarte, Andrés Octavio. “Probabilistic and constraint based modelling to determine regulation events from heterogeneous biological data : Modélisation probabiliste ou à base de contraintes pour déterminer des régulations à partir de données biologiques hétérogènes.” 2013. Doctoral Dissertation, Rennes 1; Universidad de Chile. Accessed March 28, 2020. http://www.theses.fr/2013REN1S151.

MLA Handbook (7th Edition):

Aravena Duarte, Andrés Octavio. “Probabilistic and constraint based modelling to determine regulation events from heterogeneous biological data : Modélisation probabiliste ou à base de contraintes pour déterminer des régulations à partir de données biologiques hétérogènes.” 2013. Web. 28 Mar 2020.

Vancouver:

Aravena Duarte AO. Probabilistic and constraint based modelling to determine regulation events from heterogeneous biological data : Modélisation probabiliste ou à base de contraintes pour déterminer des régulations à partir de données biologiques hétérogènes. [Internet] [Doctoral dissertation]. Rennes 1; Universidad de Chile; 2013. [cited 2020 Mar 28]. Available from: http://www.theses.fr/2013REN1S151.

Council of Science Editors:

Aravena Duarte AO. Probabilistic and constraint based modelling to determine regulation events from heterogeneous biological data : Modélisation probabiliste ou à base de contraintes pour déterminer des régulations à partir de données biologiques hétérogènes. [Doctoral Dissertation]. Rennes 1; Universidad de Chile; 2013. Available from: http://www.theses.fr/2013REN1S151


Texas Medical Center

17. Troggian Veiga, Diogo F. Systems Biology Approaches to Probe Gene Regulation in Bacteria.

Degree: PhD, 2012, Texas Medical Center

  Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory… (more)

Subjects/Keywords: Systems biology; computational biology; Mycobacterium tuberculosis; Network analysis; Gene regulation; Bioinformatics; Computational Biology; Microbiology; Systems Biology

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APA (6th Edition):

Troggian Veiga, D. F. (2012). Systems Biology Approaches to Probe Gene Regulation in Bacteria. (Doctoral Dissertation). Texas Medical Center. Retrieved from http://digitalcommons.library.tmc.edu/utgsbs_dissertations/278

Chicago Manual of Style (16th Edition):

Troggian Veiga, Diogo F. “Systems Biology Approaches to Probe Gene Regulation in Bacteria.” 2012. Doctoral Dissertation, Texas Medical Center. Accessed March 28, 2020. http://digitalcommons.library.tmc.edu/utgsbs_dissertations/278.

MLA Handbook (7th Edition):

Troggian Veiga, Diogo F. “Systems Biology Approaches to Probe Gene Regulation in Bacteria.” 2012. Web. 28 Mar 2020.

Vancouver:

Troggian Veiga DF. Systems Biology Approaches to Probe Gene Regulation in Bacteria. [Internet] [Doctoral dissertation]. Texas Medical Center; 2012. [cited 2020 Mar 28]. Available from: http://digitalcommons.library.tmc.edu/utgsbs_dissertations/278.

Council of Science Editors:

Troggian Veiga DF. Systems Biology Approaches to Probe Gene Regulation in Bacteria. [Doctoral Dissertation]. Texas Medical Center; 2012. Available from: http://digitalcommons.library.tmc.edu/utgsbs_dissertations/278


Lincoln University

18. van Loenen-den Breems, Nicoline Y. A systems biology approach to signalling pathway and gene network regulation modelling in Mastitis.

Degree: 2011, Lincoln University

 Mastitis, an inflammation in the mammary gland, is one of three major diseases in the dairy industry. One in three cows will encounter the disease… (more)

Subjects/Keywords: microarray; mastitis; RANTES; IkB; systems biology; gene network regulation; cell signalling; ODE; TNFa; NFkB; mathematical modelling; Escherichia coli; Staphylococcus aureus

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APA (6th Edition):

van Loenen-den Breems, N. Y. (2011). A systems biology approach to signalling pathway and gene network regulation modelling in Mastitis. (Thesis). Lincoln University. Retrieved from http://hdl.handle.net/10182/3925

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):

van Loenen-den Breems, Nicoline Y. “A systems biology approach to signalling pathway and gene network regulation modelling in Mastitis.” 2011. Thesis, Lincoln University. Accessed March 28, 2020. http://hdl.handle.net/10182/3925.

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

MLA Handbook (7th Edition):

van Loenen-den Breems, Nicoline Y. “A systems biology approach to signalling pathway and gene network regulation modelling in Mastitis.” 2011. Web. 28 Mar 2020.

Vancouver:

van Loenen-den Breems NY. A systems biology approach to signalling pathway and gene network regulation modelling in Mastitis. [Internet] [Thesis]. Lincoln University; 2011. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10182/3925.

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

Council of Science Editors:

van Loenen-den Breems NY. A systems biology approach to signalling pathway and gene network regulation modelling in Mastitis. [Thesis]. Lincoln University; 2011. Available from: http://hdl.handle.net/10182/3925

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


Ohio University

19. Liang, Xiaoyu. Computational Methods for Cis-Regulatory Module Discovery.

Degree: MS, Computer Science (Engineering and Technology), 2010, Ohio University

 In a gene regulation network, the action of a transcription factor binding a short region in non-coding sequence is reported and believed as the key… (more)

Subjects/Keywords: Computer Science; gene regulation network; transcription factor; non-coding sequence; gener expression; genomic sequences; cis-regulatory modules

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

APA (6th Edition):

Liang, X. (2010). Computational Methods for Cis-Regulatory Module Discovery. (Masters Thesis). Ohio University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1288578177

Chicago Manual of Style (16th Edition):

Liang, Xiaoyu. “Computational Methods for Cis-Regulatory Module Discovery.” 2010. Masters Thesis, Ohio University. Accessed March 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1288578177.

MLA Handbook (7th Edition):

Liang, Xiaoyu. “Computational Methods for Cis-Regulatory Module Discovery.” 2010. Web. 28 Mar 2020.

Vancouver:

Liang X. Computational Methods for Cis-Regulatory Module Discovery. [Internet] [Masters thesis]. Ohio University; 2010. [cited 2020 Mar 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1288578177.

Council of Science Editors:

Liang X. Computational Methods for Cis-Regulatory Module Discovery. [Masters Thesis]. Ohio University; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1288578177


Freie Universität Berlin

20. Perner, Juliane. Bioinformatische Methoden zur Untersuchung von Chromatinregulation.

Degree: 2015, Freie Universität Berlin

 Chromatin spielt eine wichtige Rolle in der Transkriptionsregulation und der Definition von Zelltypen. Die Bausteine des Chromatins, die Histonproteine, können chemisch, mit sogenannten Histonmodifikationen, verändert… (more)

Subjects/Keywords: chromatin; histone modifications; epigenetics; gene regulation; network reconstruction; computational biology; 500 Naturwissenschaften und Mathematik; 500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie

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APA (6th Edition):

Perner, J. (2015). Bioinformatische Methoden zur Untersuchung von Chromatinregulation. (Thesis). Freie Universität Berlin. Retrieved from http://dx.doi.org/10.17169/refubium-9221

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):

Perner, Juliane. “Bioinformatische Methoden zur Untersuchung von Chromatinregulation.” 2015. Thesis, Freie Universität Berlin. Accessed March 28, 2020. http://dx.doi.org/10.17169/refubium-9221.

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

MLA Handbook (7th Edition):

Perner, Juliane. “Bioinformatische Methoden zur Untersuchung von Chromatinregulation.” 2015. Web. 28 Mar 2020.

Vancouver:

Perner J. Bioinformatische Methoden zur Untersuchung von Chromatinregulation. [Internet] [Thesis]. Freie Universität Berlin; 2015. [cited 2020 Mar 28]. Available from: http://dx.doi.org/10.17169/refubium-9221.

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

Council of Science Editors:

Perner J. Bioinformatische Methoden zur Untersuchung von Chromatinregulation. [Thesis]. Freie Universität Berlin; 2015. Available from: http://dx.doi.org/10.17169/refubium-9221

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


Virginia Tech

21. Henderson, David Allen. Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis.

Degree: PhD, Genetics, 2001, Virginia Tech

 Microarray gene expression data for thousands of genes in many organisms is quickly becoming available. The information this data can provide the experimental biologist is… (more)

Subjects/Keywords: genetic regulation; gene network; microarray; factor analysis

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

APA (6th Edition):

Henderson, D. A. (2001). Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/30089

Chicago Manual of Style (16th Edition):

Henderson, David Allen. “Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis.” 2001. Doctoral Dissertation, Virginia Tech. Accessed March 28, 2020. http://hdl.handle.net/10919/30089.

MLA Handbook (7th Edition):

Henderson, David Allen. “Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis.” 2001. Web. 28 Mar 2020.

Vancouver:

Henderson DA. Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2001. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/10919/30089.

Council of Science Editors:

Henderson DA. Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis. [Doctoral Dissertation]. Virginia Tech; 2001. Available from: http://hdl.handle.net/10919/30089


University of Washington

22. Pearl, Jocelynn Renee. Systems genomics approaches in neurologic disease.

Degree: PhD, 2018, University of Washington

 Neurologic disorders encompass a broad range of diseases including neurodegenerative (Huntington's disease, Parkinson's disease, Alzheimer's), neurodevelopmental (Autism, Rett syndrome), and psychiatric or mental disorders (Schizophrenia,… (more)

Subjects/Keywords: gene regulation; Huntington's disease; network biology; neurologic disease; Systems biology; transcription factor; Molecular biology; Neurosciences; Genetics; Molecular and cellular biology

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

APA (6th Edition):

Pearl, J. R. (2018). Systems genomics approaches in neurologic disease. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40943

Chicago Manual of Style (16th Edition):

Pearl, Jocelynn Renee. “Systems genomics approaches in neurologic disease.” 2018. Doctoral Dissertation, University of Washington. Accessed March 28, 2020. http://hdl.handle.net/1773/40943.

MLA Handbook (7th Edition):

Pearl, Jocelynn Renee. “Systems genomics approaches in neurologic disease.” 2018. Web. 28 Mar 2020.

Vancouver:

Pearl JR. Systems genomics approaches in neurologic disease. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1773/40943.

Council of Science Editors:

Pearl JR. Systems genomics approaches in neurologic disease. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/40943

23. LOH YUIN HAN. Probing the Functions of Transcription Regulators in Embryonic Stem Cells.

Degree: 2008, National University of Singapore

Subjects/Keywords: Embryonic stem cell; gene regulation; epigenetic regulation; transcriptional network; self-renewal; pluripotency

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APA (6th Edition):

HAN, L. Y. (2008). Probing the Functions of Transcription Regulators in Embryonic Stem Cells. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/28154

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):

HAN, LOH YUIN. “Probing the Functions of Transcription Regulators in Embryonic Stem Cells.” 2008. Thesis, National University of Singapore. Accessed March 28, 2020. http://scholarbank.nus.edu.sg/handle/10635/28154.

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

MLA Handbook (7th Edition):

HAN, LOH YUIN. “Probing the Functions of Transcription Regulators in Embryonic Stem Cells.” 2008. Web. 28 Mar 2020.

Vancouver:

HAN LY. Probing the Functions of Transcription Regulators in Embryonic Stem Cells. [Internet] [Thesis]. National University of Singapore; 2008. [cited 2020 Mar 28]. Available from: http://scholarbank.nus.edu.sg/handle/10635/28154.

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

Council of Science Editors:

HAN LY. Probing the Functions of Transcription Regulators in Embryonic Stem Cells. [Thesis]. National University of Singapore; 2008. Available from: http://scholarbank.nus.edu.sg/handle/10635/28154

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

24. Liow, Hien-haw. Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks.

Degree: PhD, Mathematics, 2015, Washington University in St. Louis

  This dissertation explores, proposes, and examines methods of applying modernmachine learning and Bayesian statistics in the quantitative and qualitative modeling of gene regulatory networks… (more)

Subjects/Keywords: Bayesian, Gene expression, Gene regulation, Machine Learning, Network, Statistics; Mathematics

…understanding both the network structure and quantitative features of gene regulation and inform… …135 5.1.1 Non-parametric and Semi-parametric Bayesian Models for Gene Regulation… …developed to infer quantitative aspects of gene regulation relations; a parametric model is… …Introduction 1.1 Motivation A gene regulatory network (GRN) is a collection of DNA… …Level as a Function of Regulator Concentrations 2.1 Background A gene regulatory network… 

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

APA (6th Edition):

Liow, H. (2015). Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks. (Doctoral Dissertation). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/art_sci_etds/405

Chicago Manual of Style (16th Edition):

Liow, Hien-haw. “Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks.” 2015. Doctoral Dissertation, Washington University in St. Louis. Accessed March 28, 2020. https://openscholarship.wustl.edu/art_sci_etds/405.

MLA Handbook (7th Edition):

Liow, Hien-haw. “Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks.” 2015. Web. 28 Mar 2020.

Vancouver:

Liow H. Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks. [Internet] [Doctoral dissertation]. Washington University in St. Louis; 2015. [cited 2020 Mar 28]. Available from: https://openscholarship.wustl.edu/art_sci_etds/405.

Council of Science Editors:

Liow H. Application of Machine Learning to Mapping and Simulating Gene Regulatory Networks. [Doctoral Dissertation]. Washington University in St. Louis; 2015. Available from: https://openscholarship.wustl.edu/art_sci_etds/405


University of Florida

25. Bandyopadhyay, Nirmalya. Modeling Perturbations in Gene Regulatory and Signaling Networks.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2011, University of Florida

 Genes interact with each other through gene networks. A perturbation in the organism tissue can propagate to different parts of the network and affect the… (more)

Subjects/Keywords: Breast cancer; Datasets; Gene expression; Gene interaction; Genes; Mathematical independent variables; Mathematical variables; Objective functions; P values; Regulator genes; gene-regulation  – graphical-model  – machine-learning  – markov-random-field  – microarray  – perturbation  – regulatory-network  – signaling-network

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APA (6th Edition):

Bandyopadhyay, N. (2011). Modeling Perturbations in Gene Regulatory and Signaling Networks. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043564

Chicago Manual of Style (16th Edition):

Bandyopadhyay, Nirmalya. “Modeling Perturbations in Gene Regulatory and Signaling Networks.” 2011. Doctoral Dissertation, University of Florida. Accessed March 28, 2020. http://ufdc.ufl.edu/UFE0043564.

MLA Handbook (7th Edition):

Bandyopadhyay, Nirmalya. “Modeling Perturbations in Gene Regulatory and Signaling Networks.” 2011. Web. 28 Mar 2020.

Vancouver:

Bandyopadhyay N. Modeling Perturbations in Gene Regulatory and Signaling Networks. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2020 Mar 28]. Available from: http://ufdc.ufl.edu/UFE0043564.

Council of Science Editors:

Bandyopadhyay N. Modeling Perturbations in Gene Regulatory and Signaling Networks. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043564


IUPUI

26. Tripathi, Anamika. Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy.

Degree: 2017, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

Colon rectal cancer (CRC) is one of the most common cancers worldwide. It is characterized by the successive accumulation of… (more)

Subjects/Keywords: Colorectal Cancer(CRC); molecular targeted therapy; co-expression network; cetuximab treated patient; weighted gene co-expression; differentially expressed gene; co-expression module; module preservation; patient cohort; pathway analysis; epidermal growth factor receptor; vascular endothelial growth factor; transcription factor; transcriptional mi regulation; gene expression; chemotherapy

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APA (6th Edition):

Tripathi, A. (2017). Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/15338

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):

Tripathi, Anamika. “Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy.” 2017. Thesis, IUPUI. Accessed March 28, 2020. http://hdl.handle.net/1805/15338.

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

MLA Handbook (7th Edition):

Tripathi, Anamika. “Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy.” 2017. Web. 28 Mar 2020.

Vancouver:

Tripathi A. Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy. [Internet] [Thesis]. IUPUI; 2017. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1805/15338.

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

Council of Science Editors:

Tripathi A. Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy. [Thesis]. IUPUI; 2017. Available from: http://hdl.handle.net/1805/15338

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


North Carolina State University

27. Zou, Wei. Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping.

Degree: PhD, Bioinformatics, 2007, North Carolina State University

Subjects/Keywords: eQTL; Transcriptional Regulation; gene network; visualization; SVG; FDR; multiple interval mapping

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APA (6th Edition):

Zou, W. (2007). Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/5068

Chicago Manual of Style (16th Edition):

Zou, Wei. “Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping.” 2007. Doctoral Dissertation, North Carolina State University. Accessed March 28, 2020. http://www.lib.ncsu.edu/resolver/1840.16/5068.

MLA Handbook (7th Edition):

Zou, Wei. “Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping.” 2007. Web. 28 Mar 2020.

Vancouver:

Zou W. Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping. [Internet] [Doctoral dissertation]. North Carolina State University; 2007. [cited 2020 Mar 28]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5068.

Council of Science Editors:

Zou W. Transcriptional Regulatory Pattern in Yeast Revealed through Expression Quantitative Trait Locus Mapping. [Doctoral Dissertation]. North Carolina State University; 2007. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5068


Freie Universität Berlin

28. Klarner, Hannes. Beiträge zur Analyse von Qualitativen Modellen Genregulatorischer Netzwerke.

Degree: 2015, Freie Universität Berlin

 Diese Arbeit beschäftigt sich mit drei Herausforderungen, die beim Modellieren von regulatorischen Netzwerken und der Signaltransduktion auftreten. Zunächst beschreiben wir den logischen Formalismus, der von… (more)

Subjects/Keywords: boolean networks; logical network; gene regulation; signaling networks; qualitative modeling; attractors; time series; 500 Naturwissenschaften und Mathematik::510 Mathematik; 500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie

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

APA (6th Edition):

Klarner, H. (2015). Beiträge zur Analyse von Qualitativen Modellen Genregulatorischer Netzwerke. (Thesis). Freie Universität Berlin. Retrieved from http://dx.doi.org/10.17169/refubium-13160

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):

Klarner, Hannes. “Beiträge zur Analyse von Qualitativen Modellen Genregulatorischer Netzwerke.” 2015. Thesis, Freie Universität Berlin. Accessed March 28, 2020. http://dx.doi.org/10.17169/refubium-13160.

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

MLA Handbook (7th Edition):

Klarner, Hannes. “Beiträge zur Analyse von Qualitativen Modellen Genregulatorischer Netzwerke.” 2015. Web. 28 Mar 2020.

Vancouver:

Klarner H. Beiträge zur Analyse von Qualitativen Modellen Genregulatorischer Netzwerke. [Internet] [Thesis]. Freie Universität Berlin; 2015. [cited 2020 Mar 28]. Available from: http://dx.doi.org/10.17169/refubium-13160.

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

Council of Science Editors:

Klarner H. Beiträge zur Analyse von Qualitativen Modellen Genregulatorischer Netzwerke. [Thesis]. Freie Universität Berlin; 2015. Available from: http://dx.doi.org/10.17169/refubium-13160

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

29. AkhavanAghdam, Zohreh. Dynamic Signaling and Adaptation in Saccharomyces cerevisiae Stress Response Pathways.

Degree: Biology, 2017, University of California – San Diego

 Living cells respond to environmental cues through complex signaling and gene regulatory networks. A common theme throughout this thesis will be exploring design principles in… (more)

Subjects/Keywords: Biology; Dynamics; gene regulation; network motifs; Stress; transcription factor

…functions in combinatorial gene regulation. In response xiv to a transient input, either Msn2… …gene regulation by seemingly redundant TFs is not fixed, but rather dependent on the dynamics… …cells, we found that the two factors play distinct and cooperative roles in gene regulation… …similarly, indicating that this combinatorial gene regulation is not fixed and depends on the… …environments. Lastly, we sought to link Msn2/4 gene regulation to phenotypic outcome or function in… 

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APA (6th Edition):

AkhavanAghdam, Z. (2017). Dynamic Signaling and Adaptation in Saccharomyces cerevisiae Stress Response Pathways. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/9vm0b534

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):

AkhavanAghdam, Zohreh. “Dynamic Signaling and Adaptation in Saccharomyces cerevisiae Stress Response Pathways.” 2017. Thesis, University of California – San Diego. Accessed March 28, 2020. http://www.escholarship.org/uc/item/9vm0b534.

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

MLA Handbook (7th Edition):

AkhavanAghdam, Zohreh. “Dynamic Signaling and Adaptation in Saccharomyces cerevisiae Stress Response Pathways.” 2017. Web. 28 Mar 2020.

Vancouver:

AkhavanAghdam Z. Dynamic Signaling and Adaptation in Saccharomyces cerevisiae Stress Response Pathways. [Internet] [Thesis]. University of California – San Diego; 2017. [cited 2020 Mar 28]. Available from: http://www.escholarship.org/uc/item/9vm0b534.

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

Council of Science Editors:

AkhavanAghdam Z. Dynamic Signaling and Adaptation in Saccharomyces cerevisiae Stress Response Pathways. [Thesis]. University of California – San Diego; 2017. Available from: http://www.escholarship.org/uc/item/9vm0b534

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

30. Kowalczyk, Joanna E. Molecular mechanisms shaping the plant biomass utilization potential in Aspergillus.

Degree: 2017, University Utrecht

 Coordination of the induction of genes encoding extracellular enzymes and sugar uptake systems in fungi are often mediated by transcription factors (TFs). The aim of… (more)

Subjects/Keywords: Aspergillus; gene regulation; transcription factor; transcriptional network; CAZy; polysaccharide degradation

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APA (6th Edition):

Kowalczyk, J. E. (2017). Molecular mechanisms shaping the plant biomass utilization potential in Aspergillus. (Doctoral Dissertation). University Utrecht. Retrieved from http://dspace.library.uu.nl/handle/1874/356771 ; URN:NBN:NL:UI:10-1874-356771 ; urn:isbn:978-94-6295-736-7 ; URN:NBN:NL:UI:10-1874-356771 ; http://dspace.library.uu.nl/handle/1874/356771

Chicago Manual of Style (16th Edition):

Kowalczyk, Joanna E. “Molecular mechanisms shaping the plant biomass utilization potential in Aspergillus.” 2017. Doctoral Dissertation, University Utrecht. Accessed March 28, 2020. http://dspace.library.uu.nl/handle/1874/356771 ; URN:NBN:NL:UI:10-1874-356771 ; urn:isbn:978-94-6295-736-7 ; URN:NBN:NL:UI:10-1874-356771 ; http://dspace.library.uu.nl/handle/1874/356771.

MLA Handbook (7th Edition):

Kowalczyk, Joanna E. “Molecular mechanisms shaping the plant biomass utilization potential in Aspergillus.” 2017. Web. 28 Mar 2020.

Vancouver:

Kowalczyk JE. Molecular mechanisms shaping the plant biomass utilization potential in Aspergillus. [Internet] [Doctoral dissertation]. University Utrecht; 2017. [cited 2020 Mar 28]. Available from: http://dspace.library.uu.nl/handle/1874/356771 ; URN:NBN:NL:UI:10-1874-356771 ; urn:isbn:978-94-6295-736-7 ; URN:NBN:NL:UI:10-1874-356771 ; http://dspace.library.uu.nl/handle/1874/356771.

Council of Science Editors:

Kowalczyk JE. Molecular mechanisms shaping the plant biomass utilization potential in Aspergillus. [Doctoral Dissertation]. University Utrecht; 2017. Available from: http://dspace.library.uu.nl/handle/1874/356771 ; URN:NBN:NL:UI:10-1874-356771 ; urn:isbn:978-94-6295-736-7 ; URN:NBN:NL:UI:10-1874-356771 ; http://dspace.library.uu.nl/handle/1874/356771

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