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Full-Text Articles in Engineering
Towards A Dynamic View Of Genetic Networks: A Kalman Filtering Framework For Recovering Temporally-Rewiring Stable Networks From Undersampled Data, Jehandad Khan
Theses and Dissertations
It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. We refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth and cancer progression. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the networks estimation as a target tracking problem. Assuming linear dynamics, we formulate a constrained Kalman …
Development Of An Integrated Network Visualization And Graph Analysis Tool For Biological Networks, David Carbonetta
Development Of An Integrated Network Visualization And Graph Analysis Tool For Biological Networks, David Carbonetta
Theses and Dissertations
There has been steady increase in the amount of molecular data generated by experiments and computational methods performed on biological networks. There is a growing need to obtain an insight into the organization and structure of the massive and complex biological networks formed by the interacting molecules. To that end, this work presents the development of an integrated network visualization and graph analysis plugin within the Cytoscape framework. The plugin is capable of computing and visualizing a comprehensive set of dyad, node, and graph level statistics. The evaluation of the plugin on a range of biological networks and its memory …
Optimization Algorithms For Inference And Classification Of Genetic Profiles From Undersampled Measurements, Belhassen Bayar
Optimization Algorithms For Inference And Classification Of Genetic Profiles From Undersampled Measurements, Belhassen Bayar
Theses and Dissertations
In this thesis, we tackle three different problems, all related to optimization techniques for inference and classification of genetic profiles. First, we extend the deterministic Non-negative Matrix Factorization (NMF) framework to the probabilistic case (PNMF). We apply the PNMF algorithm to cluster and classify DNA microarrays data. The proposed PNMF is shown to outperform the deterministic NMF and the sparse NMF algorithms in clustering stability and classification accuracy. Second, we propose SMURC: Small-sample MUltivariate Regression with Covariance estimation. Specifically, we consider a high dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. We show that, …