Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Genomics (5)
- Medicine and Health Sciences (4)
- Biology (3)
- Integrative Biology (3)
- Biochemistry (2)
-
- Biochemistry, Biophysics, and Structural Biology (2)
- Biotechnology (2)
- Cancer Biology (2)
- Cell and Developmental Biology (2)
- Genetics (2)
- Molecular Genetics (2)
- Other Genetics and Genomics (2)
- Applied Statistics (1)
- Biochemical Phenomena, Metabolism, and Nutrition (1)
- Biological Phenomena, Cell Phenomena, and Immunity (1)
- Biometry (1)
- Biostatistics (1)
- Cell Biology (1)
- Clinical Trials (1)
- Genetic Processes (1)
- Genetic Structures (1)
- Mathematics (1)
- Medical Biomathematics and Biometrics (1)
- Medical Biotechnology (1)
- Medical Genetics (1)
- Medical Molecular Biology (1)
- Institution
- Publication Type
Articles 1 - 6 of 6
Full-Text Articles in Computational Biology
Computational Genomic Models For Spatio-Temporal Investigation Of Early Lung Cancer Pathology, Smruthy Sivakumar
Computational Genomic Models For Spatio-Temporal Investigation Of Early Lung Cancer Pathology, Smruthy Sivakumar
Dissertations & Theses (Open Access)
Lung cancer, of which non-small cell lung cancer (NSCLC) is the most common form, is the second most prevalent cancer and the leading cause of cancer-related deaths. NSCLCs primarily comprise adenocarcinomas (LUAD) and squamous cell carcinomas (LUSC). Advances in early detection and prevention have been limited by the lack of early-stage biomarkers and targets. A comprehensive molecular characterization of premalignant lesions and tumor-adjacent normal tissue can aid in better understanding NSCLC pathogenesis. However, these investigations are further challenged by limited tissue availability and low cellular fractions of detectable somatic mutations.
Therefore, there is a dearth of knowledge about the pathogenesis …
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
COBRA Preprint Series
One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …
Supervised Dimension Reduction For Large-Scale "Omics" Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards, Lauren Spirko-Burns, Karthik Devarajan
Supervised Dimension Reduction For Large-Scale "Omics" Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards, Lauren Spirko-Burns, Karthik Devarajan
COBRA Preprint Series
The past two decades have witnessed significant advances in high-throughput ``omics" technologies such as genomics, proteomics, metabolomics, transcriptomics and radiomics. These technologies have enabled simultaneous measurement of the expression levels of tens of thousands of features from individual patient samples and have generated enormous amounts of data that require analysis and interpretation. One specific area of interest has been in studying the relationship between these features and patient outcomes, such as overall and recurrence-free survival, with the goal of developing a predictive ``omics" profile. Large-scale studies often suffer from the presence of a large fraction of censored observations and potential …
Accurate Mutation Annotation And Functional Prediction Enhance The Applicability Of -Omics Data In Precision Medicine, Tenghui Chen
Accurate Mutation Annotation And Functional Prediction Enhance The Applicability Of -Omics Data In Precision Medicine, Tenghui Chen
Dissertations & Theses (Open Access)
Clinical sequencing has been recognized as an effective approach for enhancing the accuracy and efficiency of cancer patient management and therefore achieve the goals of personalized therapy. However, the accuracy of large scale sequencing data in clinics has been constrained by many different aspects, such as clinical detection, annotation and interpretation of the variants that are observed in clinical sequencing data. In my Ph.D thesis work, I mainly investigated how to comprehensively and efficiently apply high dimensional -omics data to enhance the capability of precision cancer medicine. Following this motivation, my dissertation has been focused on two important topics in …
Investigating Metastatic Lineage In Colorectal Cancer By Single Cell Dna Sequencing, Marco Leung
Investigating Metastatic Lineage In Colorectal Cancer By Single Cell Dna Sequencing, Marco Leung
Dissertations & Theses (Open Access)
Metastasis is the primary cause of human cancer deaths. Patients with metastatic colorectal cancer (mCRC) show only an 11% 5-year survival rate, compared to those without local or distant metastases (92% 5-year survival rate). Understanding the CRC tumor evolution may provide valuable insights on how to improve treatment in patients with mCRC. However, the genomic basis of metastasis has been difficult to study, in part due to the extensive intratumor heterogeneity at both the primary and metastatic tumor sites, and the low frequency of subclones with metastatic potential. Previous studies have applied conventional bulk next-generation sequencing (NGS) methods, which have …
Genomic Characterization Of Polyps In Familial Adenomatous Polyposis Patients And Identification Of Candidate Chemopreventive Drugs, Francis A. San Lucas
Genomic Characterization Of Polyps In Familial Adenomatous Polyposis Patients And Identification Of Candidate Chemopreventive Drugs, Francis A. San Lucas
Dissertations & Theses (Open Access)
Familial adenomatous polyposis (FAP) is an autosomal dominant disease characterized by APC germline mutations and the development of hundreds to thousands of premalignant adenomas in the gastrointestinal tract at a young age. If left untreated, these patients inevitably develop colon cancer (CRC) and small bowel tumors. We performed exome sequencing of samples from 12 FAP patients to characterize adenomas and to identify candidate genes of adenoma development that may serve as potential targets for chemoprevention drug development. From each patient, a blood and at least one polyp were sequenced with a total of 25 polyps analyzed. In some cases, normal …