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Other Computer Engineering

Graduate Theses, Dissertations, and Problem Reports

Boolean Implication Networks

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A Novel Computational Network Methodology For Discovery Of Biomarkers And Therapeutic Targets, Qing Ye Jan 2022

A Novel Computational Network Methodology For Discovery Of Biomarkers And Therapeutic Targets, Qing Ye

Graduate Theses, Dissertations, and Problem Reports

Lung cancer has the second highest cancer incidence rate and the top cancer-related mortality worldwide. An estimate from the American Cancer Society shows that, in 2022, there will be about 236,740 lung cancer cases (117,910 men and 118,830 women) in the US. To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. There is an unmet clinical need to identify patients with early-stage NSCLC who are likely to develop recurrence and to predict their therapeutic responses. This dissertation developed a novel computational methodology for modeling molecular gene association networks …


Genet-Cnv: Boolean Implication Networks For Modeling Genome-Wide Co-Occurrence Of Dna Copy Number Variations, Salvi Singh Jan 2019

Genet-Cnv: Boolean Implication Networks For Modeling Genome-Wide Co-Occurrence Of Dna Copy Number Variations, Salvi Singh

Graduate Theses, Dissertations, and Problem Reports

Lung cancer is the leading cause of cancer-related death in the world. Lung cancer can be categorized as non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC makes up about 80% to 85% of lung cancer cases diagnosed, whereas SCLC is responsible for 10% to 15% of the cases. It remains a challenge for physicians to identify patients who shall benefit from chemotherapy. In such a scenario, identifying genes that can facilitate therapeutic target discoveries and better understanding disease mechanisms and their regulation in different stages of lung cancer, remains an important topic of research.

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