Although genomewide RNA expression analysis has become a routine tool in biomedical
research, extracting biological insight from such information remains a major challenge. Here, …

We introduce a statistic, the persistent homology transform (PHT), to model surfaces in ${\mathbb
{ R}}^3$ and shapes in ${\mathbb { R}}^2$ . This statistic is a collection of persistence …

The problem of automatically tuning multiple parameters for pattern recognition Support
Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the …

A statistical methodology for estimating dataset size requirements for classifying microarray
data using learning curves is introduced. The goal is to use existing classification results to …

Using advanced gene targeting methods, generating mouse models of cancer that accurately
reproduce the genetic alterations present in human tumors is now relatively straightforward…

Searching for genetic variants with unusual differentiation between subpopulations is an
established approach for identifying signals of natural selection. However, existing methods …

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by
using a complex combination of clinical and histopathological data. In some instances, this …

We introduce a method of feature selection for Support Vector Machines. The method is
based upon finding those features which minimize bounds on the leave-one-out error. This …

A novel method for regression has been recently proposed by Vapnik et al. (1995, 1996).
The technique, called support vector machine (SVM), is very well founded from the …

Background Clinical trials have indicated a benefit of adjuvant chemotherapy for patients
with stage IB, II, or IIIA — but not stage IA — non–small-cell lung cancer (NSCLC). This …