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Articles 1 - 6 of 6
Full-Text Articles in Systems Biology
Gene Expression–Based Algorithms For The Identification Of Drug Combinations In Personalized Medicine, Lon Fong
Dissertations and 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 …
Public Discussion Of Anthrax On Twitter: Using Machine Learning To Identify Relevant Topics And Events, Michele Miller, William Lee Romine, Terry L. Oroszi
Public Discussion Of Anthrax On Twitter: Using Machine Learning To Identify Relevant Topics And Events, Michele Miller, William Lee Romine, Terry L. Oroszi
Biological Sciences Faculty Publications
Background: Social media allows researchers to study opinions and reactions to events in real time. One area needing more study is anthrax-related events. A computational framework that utilizes machine learning techniques was created to collect tweets discussing anthrax, further categorize them as relevant by the month of data collection, and detect discussions on anthrax-related events. Objective: The objective of this study was to detect discussions on anthrax-related events and to determine the relevance of thetweets and topics of discussion over 12 months of data collection. Methods: This is an infoveillance study, using tweets in English containing the keyword “Anthrax” and …
Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande
Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande
KGI Theses and Dissertations
Huntington’s disease (HD) is a debilitating neurodegenerative disorder with a complex pathophysiology. Despite extensive studies to study the disease, the sequence of events through which mutant Huntingtin (mHtt) protein executes its action still remains elusive. The phenotype of HD is an outcome of numerous processes initiated by the mHtt protein along with other proteins that act as either suppressors or enhancers of the effects of mHtt protein and PolyQ aggregates. Utilizing an integrative systems biology approach, I construct and analyze a Huntington’s disease integrome using human orthologs of protein interactors of wild type and mHtt protein. Analysis of this integrome …
Global Gene Expression Profiling Of Healthy Human Brain And Its Application In Studying Neurological Disorders, Simarjeet K. Negi
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 …
Computational Labeling, Partitioning, And Balancing Of Molecular Networks, Biaobin Jiang
Computational Labeling, Partitioning, And Balancing Of Molecular Networks, Biaobin Jiang
Open Access Dissertations
Recent advances in high throughput techniques enable large-scale molecular quantification with high accuracy, including mRNAs, proteins and metabolites. Differential expression of these molecules in case and control samples provides a way to select phenotype-associated molecules with statistically significant changes. However, given the significance ranking list of molecular changes, how those molecules work together to drive phenotype formation is still unclear. In particular, the changes in molecular quantities are insufficient to interpret the changes in their functional behavior. My study is aimed at answering this question by integrating molecular network data to systematically model and estimate the changes of molecular functional …
Classification Of Breast Cancer Patients Using Somatic Mutation Profiles And Machine Learning Approaches, Suleyman Vural
Classification Of Breast Cancer Patients Using Somatic Mutation Profiles And Machine Learning Approaches, Suleyman Vural
Theses & Dissertations
The high degree of heterogeneity observed in breast cancers makes it very difficult to classify cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. In this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Identified somatic and non-synonymous single nucleotide variants were assigned a quantitative score (C-score) that represents the extent of negative impact on the function of the gene. Using …