Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Bayesian statistics (1)
- Biomarkers (1)
- Biomarkers. Breast cancer. Classification. Lymph nodes. Machine learning. Neural network (1)
- Breast cancer (1)
- Classification (1)
-
- Custom CDF (1)
- Drug repurposing (1)
- Gene expression (1)
- Generalized linear model (1)
- Hungarian algorithm (1)
- Imputation (1)
- Interactome (1)
- Lymph nodes (1)
- Machine learning (1)
- Mass spectrometry (1)
- Metabolomics (1)
- Microarrays (1)
- Negative binomial distribution (1)
- Neural network (1)
- Perturbation gene expression (1)
- Probe group (1)
- Probeset (1)
- Protein-protein interaction (PPI) networks (1)
- Reporting Odds Ratio (1)
- Statistics (1)
- Technical variability (1)
- Tissue extraction (1)
- Tissue storage (1)
- UTR (1)
Articles 1 - 7 of 7
Full-Text Articles in Bioinformatics
A Network-Based Approach For Computational Drug Repurposing On Cancer Data, Ann Reba, Thomas Alexander
A Network-Based Approach For Computational Drug Repurposing On Cancer Data, Ann Reba, Thomas Alexander
Electronic Theses and Dissertations
In this thesis, we are interested in finding the best drugs that can be repurposed for the disease and able to find the adverse effects such drugs that are FDA-Approved. Developing an effective drug can be a time-consuming and expensive crucible method. Network-based machine learning methods are used for predicting a given drug for A that can be used for B. It aims at finding new indications for already existing drugs and therefore increases the available therapeutic choices at a fraction of the cost of new drug development. The perturbation gene expression data corresponding to the MCF7 cell line was …
Deep Learning Applications In Medical Bioinformatics, Ziad Omar
Deep Learning Applications In Medical Bioinformatics, Ziad Omar
Electronic Theses and Dissertations
After a patient’s breast cancer diagnosis, identifying breast cancer lymph node metastases is one of the most important and critical factor that is directly related to the patient’s survival. The traditional way to examine the existence of cancer cells in the breast lymph nodes is through a lymph node procedure, biopsy. The procedure process is time-consuming for the patient and the provider, costly, and lacks accuracy as not every lymph node is examined. The intent of this study is to develop an artificial neural network (ANNs) that would map genetic biomarkers to breast lymph node classes using ANNs. The neural …
A Network-Based Approach For Computational Drug Repurposing On Cancer Data, Ann Reba Thomas Alexander
A Network-Based Approach For Computational Drug Repurposing On Cancer Data, Ann Reba Thomas Alexander
Electronic Theses and Dissertations
In this thesis, we are interested in finding the best drugs that can be repurposed for the disease and able to find the adverse effects such drugs that are FDA-Approved. Developing an effective drug can be a time-consuming and expensive crucible method. Network-based machine learning methods are used for predicting a given drug for A that can be used for B. It aims at finding new indications for already existing drugs and therefore increases the available therapeutic choices at a fraction of the cost of new drug development. The perturbation gene expression data corresponding to the MCF7 cell line was …
Deep Learning Applications In Medical Bioinformatics, Ziad Omar
Deep Learning Applications In Medical Bioinformatics, Ziad Omar
Electronic Theses and Dissertations
After a patient’s breast cancer diagnosis, identifying breast cancer lymph node metastases is one of the most important and critical factor that is directly related to the patient’s survival. The traditional way to examine the existence of cancer cells in the breast lymph nodes is through a lymph node procedure, biopsy. The procedure process is time-consuming for the patient and the provider, costly, and lacks accuracy as not every lymph node is examined. The intent of this study is to develop an artificial neural network (ANNs) that would map genetic biomarkers to breast lymph node classes using ANNs. The neural …
Designing And Sample Size Calculation In Presence Of Heterogeneity In Biological Studies Involving High-Throughput Data., Sudhir Srivastava
Designing And Sample Size Calculation In Presence Of Heterogeneity In Biological Studies Involving High-Throughput Data., Sudhir Srivastava
Electronic Theses and Dissertations
The designing and determination of sample size are important for conducting high-throughput biological experiments such as proteomics experiments and RNA-Seq expression studies, thus leading to better understanding of complex mechanisms underlying various biological processes. The variations in the biological data or technical approaches to data collection lead to heterogeneity for the samples under study. We critically worked on the issues of technical and biological heterogeneity. The quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values (MVs) and data heterogeneity. We considered a proteomics data set generated from human kidney …
Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor
Electronic Theses and Dissertations
Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …
Region Based Gene Expression Via Reanalysis Of Publicly Available Microarray Data Sets., Ernur Saka
Region Based Gene Expression Via Reanalysis Of Publicly Available Microarray Data Sets., Ernur Saka
Electronic Theses and Dissertations
A DNA microarray is a high-throughput technology used to identify relative gene expression. One of the most widely used platforms is the Affymetrix® GeneChip® technology which detects gene expression levels based on probe sets composed of a set of twenty-five nucleotide probes designed to hybridize with specific gene targets. Given a particular Affymetrix® GeneChip® platform, the design of the probes is fixed. However, the method of analysis is dynamic in nature due to the ability to annotate and group probes into uniquely defined groupings. This is particularly important since publicly available repositories of microarray datasets, such as ArrayExpress and NCBI’s …