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Spring 2024
As cancer is the leading global cause of death, an ongoing challenge is predicting an individual's cancer progression accurately, to facilitate personalized treatment planning. Individuals diagnosed with cancer may succumb to the illness or face cancer recurrence post-treatment. The first part of...
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Detecting, correcting, and preventing the batch effects in multi-site data, with a focus on gene expression Microarrays
DownloadSpring 2014
Gene expression microarrays are widely used to better understand the complex biological mechanisms inside cells. One of the main obstacles of applying statistical learning algorithms to microarray data is the large gap between the number of features (p) and the number of available instances (n),...
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Spring 2012
Recent advances in high-throughput technologies, such as genome-wide SNP analysis and microar- ray gene expression profiling, have led to a multitude of ranked lists, where the features (SNPs, genes) are sorted based on their individual correlation with a phenotype. Multiple reviews have shown...
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Learning in silico Reactant and Bond-of-Metabolism Predictors for Human Cytochrome P450 Enzymes
DownloadFall 2019
Human beings are exposed to many chemicals through their routine interactions with the environment, such as food/drug consumption, household or workplace activities, industrial or transportation activities, and even common environmental processes. Once absorbed, these chemicals are usually...
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Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Diagnose ADHD and Autism
DownloadFall 2014
A clinical tool that can diagnose psychiatric illness using functional or structural magnetic resonance (MR) brain images would greatly assist physicians. Here, we propose a learning algorithm that uses the histogram of oriented gradients (HOG) features of MR brain images, as well as personal...