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Gene expression

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Articles 1 - 7 of 7

Full-Text Articles in Systems Biology

Modeling Nonsegmented Negative-Strand Rna Virus (Nnsv) Transcription With Ejective Polymerase Collisions And Biased Diffusion, Felipe-Andres Piedra Sep 2023

Modeling Nonsegmented Negative-Strand Rna Virus (Nnsv) Transcription With Ejective Polymerase Collisions And Biased Diffusion, Felipe-Andres Piedra

Research Symposium

Background: The textbook model of NNSV transcription predicts a gene expression gradient. However, multiple studies show non-gradient gene expression patterns or data inconsistent with a simple gradient. Regarding the latter, several studies show a dramatic decrease in gene expression over the last two genes of the respiratory syncytial virus (RSV) genome (a highly studied NNSV). The textbook model cannot explain these phenomena.

Methods: Computational models of RSV and vesicular stomatitis virus (VSV – another highly studied NNSV) transcription were written in the Python programming language using the Scientific Python Development Environment. The model code is freely available on GitHub: …


Gene Expression–Based Algorithms For The Identification Of Drug Combinations In Personalized Medicine, Lon Fong May 2023

Gene Expression–Based Algorithms For The Identification Of Drug Combinations In Personalized Medicine, Lon Fong

Dissertations & Theses (Open Access)

Three of the major problems facing cancer therapeutics are 1) drug resistance, the intrinsic or acquired ability of cancer cells to evade the effect of the therapies used to treat them; 2) heterogeneity among individual patients’ disease at the molecular level and the resulting variability in therapeutic response; and 3) the limitations of genomics biomarkers in matching patients to the most effective therapy. One possible solution to drug resistance is the use of combination therapies rather than monotherapies. Use of multiple drugs, each with a different mechanism of action, lowers the chances that the cancer cells will develop or have …


Periodic Spatial Disturbances Alter The Expression Of Quorum Sensing Virulence Factors In Pseudomonas Aeruginosa, Laura García-Diéguez Apr 2022

Periodic Spatial Disturbances Alter The Expression Of Quorum Sensing Virulence Factors In Pseudomonas Aeruginosa, Laura García-Diéguez

All HCAS Student Capstones, Theses, and Dissertations

Pseudomonas aeruginosa is an opportunistic pathogen associated with severe acute and chronic illnesses. Current antibiotic-based approaches fail to effectively treat P. aeruginosa infections due to the effectiveness and robustness of the quorum sensing signaling system (QS). Pathogenic bacteria, such as P. aeruginosa, employ this population density-dependent communication mechanism to confer antimicrobial resistance, propagate infection, and coordinate the expression of virulence factors, through the production and detection of autoinducing signaling molecules (AI). As such, there is a growing interest in developing novel non-antibiotic-based techniques to attenuate the pathogenicity of P. aeruginosa by disrupting the functionality of its QS system. Previous …


Biological Pathway Involvement In Melanoma Heterogeneity And Drug-Induced Resistance, Sarah V. Pack Aug 2019

Biological Pathway Involvement In Melanoma Heterogeneity And Drug-Induced Resistance, Sarah V. Pack

STAR Program Research Presentations

Tumors develop resistance to numerous drug therapies, and this remains a major obstacle in treating many types of non-surgical cancers. Melanoma provides a good model system for studying drug resistance in cancer due to its high propensity to incur resistance after a significant initial response to a drug. Genes that are highly expressed in melanoma cancer cells have been studied, but in order to further understand the collective function of these highly expressed genes we must analyze gene sets, or pathways. A single gene’s function is rarely independent of other genes, and pathway analysis takes this into account.

Our objective …


Global Gene Expression Profiling Of Healthy Human Brain And Its Application In Studying Neurological Disorders, Simarjeet K. Negi Dec 2016

Global Gene Expression Profiling Of Healthy Human Brain And Its Application In Studying Neurological Disorders, Simarjeet K. Negi

Theses & Dissertations

The human brain is the most complex structure known to mankind and one of the greatest challenges in modern biology is to understand how it is built and organized. The power of the brain arises from its variety of cells and structures, and ultimately where and when different genes are switched on and off throughout the brain tissue. In other words, brain function depends on the precise regulation of gene expression in its sub-anatomical structures. But, our understanding of the complexity and dynamics of the transcriptome of the human brain is still incomplete. To fill in the need, we designed …


Transcriptome Analysis Of Vaccine Responses To Francisella Tularensis Or Venezuelan Equine Encephalitis Virus, Rebecca Ann Erwin-Cohen Jan 2016

Transcriptome Analysis Of Vaccine Responses To Francisella Tularensis Or Venezuelan Equine Encephalitis Virus, Rebecca Ann Erwin-Cohen

Walden Dissertations and Doctoral Studies

The lack of vaccines for emerging and re-emerging diseases highlights technical gaps and indicates a need for innovative approaches to produce new vaccines. Vaccines may be improved by knowledge of host responses to vaccination, disease pathogenesis, and the effect of age and genetics on vaccine outcome. This study's purpose was to quantitatively assess the molecular epidemiology of Francisella tularensis (Ft) and Venezuelan Equine Encephalitis Virus (VEEV). Study results support the Epidemiology Nexus model which holds that association of changes in gene expression to vaccination facilitate understanding the mechanisms of immune development and link public health and disease epidemiology. My research …


Integration Of Breast Cancer Gene Signatures Based On Graph Centrality, Jianxin Wang, Gang Chen, Min Li, Yi Pan Jan 2011

Integration Of Breast Cancer Gene Signatures Based On Graph Centrality, Jianxin Wang, Gang Chen, Min Li, Yi Pan

Computer Science Faculty Publications

Background: Various gene-expression signatures for breast cancer are available for the prediction of clinical outcome. However due to small overlap between different signatures, it is challenging to integrate existing disjoint signatures to provide a unified insight on the association between gene expression and clinical outcome.

Results: In this paper, we propose a method to integrate different breast cancer gene signatures by using graph centrality in a context-constrained protein interaction network (PIN). The context-constrained PIN for breast cancer is built by integrating complete PIN and various gene signatures reported in literatures. Then, we use graph centralities to quantify the importance of …