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You searched for +publisher:"Georgia State University" +contributor:("Remus Osan"). Showing records 1 – 8 of 8 total matches.

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Georgia State University

1. Zhang, Jie. Analysis of traveling wave propagation in one-dimensional integrate-and-fire neural networks.

Degree: PhD, Mathematics and Statistics, 2016, Georgia State University

  One-dimensional neural networks comprised of large numbers of Integrate-and-Fire neurons have been widely used to model electrical activity propagation in neural slices. Despite these… (more)

Subjects/Keywords: Traveling waves; Integrate-and-fire neuron model; Propagation failure; Differential equations; Speed approximations; Numerical simulation

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APA (6th Edition):

Zhang, J. (2016). Analysis of traveling wave propagation in one-dimensional integrate-and-fire neural networks. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_diss/36

Chicago Manual of Style (16th Edition):

Zhang, Jie. “Analysis of traveling wave propagation in one-dimensional integrate-and-fire neural networks.” 2016. Doctoral Dissertation, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/math_diss/36.

MLA Handbook (7th Edition):

Zhang, Jie. “Analysis of traveling wave propagation in one-dimensional integrate-and-fire neural networks.” 2016. Web. 19 Aug 2019.

Vancouver:

Zhang J. Analysis of traveling wave propagation in one-dimensional integrate-and-fire neural networks. [Internet] [Doctoral dissertation]. Georgia State University; 2016. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/math_diss/36.

Council of Science Editors:

Zhang J. Analysis of traveling wave propagation in one-dimensional integrate-and-fire neural networks. [Doctoral Dissertation]. Georgia State University; 2016. Available from: https://scholarworks.gsu.edu/math_diss/36


Georgia State University

2. Chang, Regina. Identifying Inflammatory Bowel Disease Patients in TCGA Database.

Degree: MS, Mathematics and Statistics, 2016, Georgia State University

  Chronic inflammation increases the risk of developing cancer. We aim to investigate the molecular pathway of inflammation induced cancer by comparing gene expression in… (more)

Subjects/Keywords: TCGA; microarray; Cancer; Inflammation; CRC; Colon Rectal Cancer; IBD

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APA (6th Edition):

Chang, R. (2016). Identifying Inflammatory Bowel Disease Patients in TCGA Database. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_theses/154

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):

Chang, Regina. “Identifying Inflammatory Bowel Disease Patients in TCGA Database.” 2016. Thesis, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/math_theses/154.

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

MLA Handbook (7th Edition):

Chang, Regina. “Identifying Inflammatory Bowel Disease Patients in TCGA Database.” 2016. Web. 19 Aug 2019.

Vancouver:

Chang R. Identifying Inflammatory Bowel Disease Patients in TCGA Database. [Internet] [Thesis]. Georgia State University; 2016. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/math_theses/154.

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

Council of Science Editors:

Chang R. Identifying Inflammatory Bowel Disease Patients in TCGA Database. [Thesis]. Georgia State University; 2016. Available from: https://scholarworks.gsu.edu/math_theses/154

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


Georgia State University

3. Xia, Jun. Statistical Models and Analysis of Growth Processes in Biological Tissue.

Degree: PhD, Mathematics and Statistics, 2016, Georgia State University

  The mechanisms that control growth processes in biology tissues have attracted continuous research interest despite their complexity. With the emergence of big data experimental… (more)

Subjects/Keywords: Neuronal Tree; Stochastic Models; Maximum Length Constraint; Tumor Size Growth Rate; Survival Analysis; Model Selection

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APA (6th Edition):

Xia, J. (2016). Statistical Models and Analysis of Growth Processes in Biological Tissue. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_diss/39

Chicago Manual of Style (16th Edition):

Xia, Jun. “Statistical Models and Analysis of Growth Processes in Biological Tissue.” 2016. Doctoral Dissertation, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/math_diss/39.

MLA Handbook (7th Edition):

Xia, Jun. “Statistical Models and Analysis of Growth Processes in Biological Tissue.” 2016. Web. 19 Aug 2019.

Vancouver:

Xia J. Statistical Models and Analysis of Growth Processes in Biological Tissue. [Internet] [Doctoral dissertation]. Georgia State University; 2016. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/math_diss/39.

Council of Science Editors:

Xia J. Statistical Models and Analysis of Growth Processes in Biological Tissue. [Doctoral Dissertation]. Georgia State University; 2016. Available from: https://scholarworks.gsu.edu/math_diss/39


Georgia State University

4. Barnett, William. Mechanisms of the Coregulation of Multiple Ionic Currents for the Control of Neuronal Activity.

Degree: PhD, Neuroscience Institute, 2015, Georgia State University

  An open question in contemporary neuroscience is how neuromodulators coregulate multiple conductances to maintain functional neuronal activity. Neuromodulators enact changes to properties of biophysical… (more)

Subjects/Keywords: Bursting; Central pattern generator; Neuromodulation

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APA (6th Edition):

Barnett, W. (2015). Mechanisms of the Coregulation of Multiple Ionic Currents for the Control of Neuronal Activity. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/neurosci_diss/18

Chicago Manual of Style (16th Edition):

Barnett, William. “Mechanisms of the Coregulation of Multiple Ionic Currents for the Control of Neuronal Activity.” 2015. Doctoral Dissertation, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/neurosci_diss/18.

MLA Handbook (7th Edition):

Barnett, William. “Mechanisms of the Coregulation of Multiple Ionic Currents for the Control of Neuronal Activity.” 2015. Web. 19 Aug 2019.

Vancouver:

Barnett W. Mechanisms of the Coregulation of Multiple Ionic Currents for the Control of Neuronal Activity. [Internet] [Doctoral dissertation]. Georgia State University; 2015. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/neurosci_diss/18.

Council of Science Editors:

Barnett W. Mechanisms of the Coregulation of Multiple Ionic Currents for the Control of Neuronal Activity. [Doctoral Dissertation]. Georgia State University; 2015. Available from: https://scholarworks.gsu.edu/neurosci_diss/18

5. tian, siyu. A Mathematical Model For Population Dynamics of Antibiotic Treatment.

Degree: MS, Mathematics and Statistics, 2014, Georgia State University

  The objective of the thesis is to model the behavior of the reaction between two species of bacteria and antibiotics by building an ordinary… (more)

Subjects/Keywords: Ordinary Differential Equations; Population dynamics; Multiple species Bacteria; Antibiotics; Simulation; Equilibrium Points

…analysis came from Dr. Eric Gilbert’s lab of the Biology department at Georgia State University… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7 Sample image

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APA (6th Edition):

tian, s. (2014). A Mathematical Model For Population Dynamics of Antibiotic Treatment. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_theses/142

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):

tian, siyu. “A Mathematical Model For Population Dynamics of Antibiotic Treatment.” 2014. Thesis, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/math_theses/142.

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

MLA Handbook (7th Edition):

tian, siyu. “A Mathematical Model For Population Dynamics of Antibiotic Treatment.” 2014. Web. 19 Aug 2019.

Vancouver:

tian s. A Mathematical Model For Population Dynamics of Antibiotic Treatment. [Internet] [Thesis]. Georgia State University; 2014. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/math_theses/142.

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

Council of Science Editors:

tian s. A Mathematical Model For Population Dynamics of Antibiotic Treatment. [Thesis]. Georgia State University; 2014. Available from: https://scholarworks.gsu.edu/math_theses/142

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

6. Nieto, Bernardo. Accurate Approximation Series for Optimal Targeting Regions in a Neural Growth Model with a Low –branching Probability.

Degree: MS, Mathematics and Statistics, 2015, Georgia State University

  Understanding the complex growth process of dendritic arbors is essential for the medical field and disciplines like Biology and Neurosciences. The establishment of the… (more)

Subjects/Keywords: Growth of neural trees; Computational model; Stochastic branching probability; Expected number of active branches; Variances; Recurrence formula

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APA (6th Edition):

Nieto, B. (2015). Accurate Approximation Series for Optimal Targeting Regions in a Neural Growth Model with a Low –branching Probability. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_theses/150

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):

Nieto, Bernardo. “Accurate Approximation Series for Optimal Targeting Regions in a Neural Growth Model with a Low –branching Probability.” 2015. Thesis, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/math_theses/150.

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

MLA Handbook (7th Edition):

Nieto, Bernardo. “Accurate Approximation Series for Optimal Targeting Regions in a Neural Growth Model with a Low –branching Probability.” 2015. Web. 19 Aug 2019.

Vancouver:

Nieto B. Accurate Approximation Series for Optimal Targeting Regions in a Neural Growth Model with a Low –branching Probability. [Internet] [Thesis]. Georgia State University; 2015. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/math_theses/150.

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

Council of Science Editors:

Nieto B. Accurate Approximation Series for Optimal Targeting Regions in a Neural Growth Model with a Low –branching Probability. [Thesis]. Georgia State University; 2015. Available from: https://scholarworks.gsu.edu/math_theses/150

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

7. Xing, Tingli. Computational Study in Chaotic Dynamical Systems and Mechanisms for Pattern Generation in Three-Cell Networks.

Degree: PhD, Mathematics and Statistics, 2015, Georgia State University

  A computational technique is introduced to reveal the complex intrinsic structure of homoclinic and heteroclinic bifurcations in a chaotic dynamical system. This technique is… (more)

Subjects/Keywords: Saddle; Saddle-focus; Lorenz attractor; Chaos; Escape; CPG

…xii LIST OF ABBREVIATIONS • CPG - Central Pattern Generator • GSU - Georgia State… …University • HB - Homoclinic Bifurcation • PM - Pace-Maker • TW - Traveling-Wave • SM - Shimizu… 

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APA (6th Edition):

Xing, T. (2015). Computational Study in Chaotic Dynamical Systems and Mechanisms for Pattern Generation in Three-Cell Networks. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_diss/27

Chicago Manual of Style (16th Edition):

Xing, Tingli. “Computational Study in Chaotic Dynamical Systems and Mechanisms for Pattern Generation in Three-Cell Networks.” 2015. Doctoral Dissertation, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/math_diss/27.

MLA Handbook (7th Edition):

Xing, Tingli. “Computational Study in Chaotic Dynamical Systems and Mechanisms for Pattern Generation in Three-Cell Networks.” 2015. Web. 19 Aug 2019.

Vancouver:

Xing T. Computational Study in Chaotic Dynamical Systems and Mechanisms for Pattern Generation in Three-Cell Networks. [Internet] [Doctoral dissertation]. Georgia State University; 2015. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/math_diss/27.

Council of Science Editors:

Xing T. Computational Study in Chaotic Dynamical Systems and Mechanisms for Pattern Generation in Three-Cell Networks. [Doctoral Dissertation]. Georgia State University; 2015. Available from: https://scholarworks.gsu.edu/math_diss/27

8. Collens, Jarod. Rhythmogenesis and Bifurcation Analysis of 3-Node Neural Network Kernels.

Degree: PhD, Neuroscience Institute, 2017, Georgia State University

  Central pattern generators (CPGs) are small neural circuits of coupled cells stably producing a range of multiphasic coordinated rhythmic activities like locomotion, heartbeat, and… (more)

Subjects/Keywords: Network dynamics; Fitzhugh-Nagumo; Dynamical systems; Bifurcation analysis; 3-cell inhibitory networks; Modular networking

…dissertation committee: Dr. Remus Osan, Dr. Igor Belykh, and Dr. Astrid Prinz for their time, insight… 

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APA (6th Edition):

Collens, J. (2017). Rhythmogenesis and Bifurcation Analysis of 3-Node Neural Network Kernels. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/neurosci_diss/28

Chicago Manual of Style (16th Edition):

Collens, Jarod. “Rhythmogenesis and Bifurcation Analysis of 3-Node Neural Network Kernels.” 2017. Doctoral Dissertation, Georgia State University. Accessed August 19, 2019. https://scholarworks.gsu.edu/neurosci_diss/28.

MLA Handbook (7th Edition):

Collens, Jarod. “Rhythmogenesis and Bifurcation Analysis of 3-Node Neural Network Kernels.” 2017. Web. 19 Aug 2019.

Vancouver:

Collens J. Rhythmogenesis and Bifurcation Analysis of 3-Node Neural Network Kernels. [Internet] [Doctoral dissertation]. Georgia State University; 2017. [cited 2019 Aug 19]. Available from: https://scholarworks.gsu.edu/neurosci_diss/28.

Council of Science Editors:

Collens J. Rhythmogenesis and Bifurcation Analysis of 3-Node Neural Network Kernels. [Doctoral Dissertation]. Georgia State University; 2017. Available from: https://scholarworks.gsu.edu/neurosci_diss/28

.