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A common challenge in the analysis of genomics data is trying to understand the underlying phenomenon in the context of all complex interactions taking place on various signaling pathways. A statistical approach using various models is universally used to identify the most relevant pathways in a given experiment. Here, we show that the existing pathway(More)
Onto-Tools is a freely available web-accessible software suite, composed of an annotation database and nine complementary data-mining tools. This article describes a new tool, Onto-Express-to-go (OE2GO), as well as some new features implemented in Pathway-Express and Onto-Miner over the past year. Pathway-Express (PE) has been enhanced to identify(More)
The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various(More)
Identification of the most impacted signaling pathways in a given condition is a crucial step in understanding the underlying biological mechanism. An impact analysis that is able to take in consideration the structure of a given signaling pathway was proposed to measure the impact on each pathway given a list of differentially expressed (DE) genes and(More)
Like most classification techniques, the existing support vector machines (SVM) approaches are challenged to correctly classify their input when the data points are either very close to the decision boundary or very dissimilar from the training data set. In both situations, most classifiers including SVMs will still give a prediction by assigning the test(More)
High throughput technologies enable researchers to measure expression levels on a genomic scale. However, the correct and efficient biological interpretation of such voluminous data remains a challenging problem. Many tools have been developed for the analysis of GO terms that are over- or under-represented in a list of differentially expressed genes.(More)
OBJECTIVES/HYPOTHESIS A reliable estimate of survival is important as it may impact treatment choice. The objective of this study is to identify serum autoantibody biomarkers that can be used to improve prognostication for patients affected with head and neck squamous cell carcinoma (HNSCC). STUDY DESIGN Prospective cohort study. METHODS A panel of 130(More)