show that the compendium tional responses to the perturbation of most cellular can be used to characterize pharmacological perturpathways, systematic characterization of novel mutants bations by identifying a novel target of the commonly could be carried out with a single genome-wide expresused drug

available training examples from cancer and normal patients, we build a classifier suitable for genetic diagnosis, as well as drug discovery. Previous attempts to address this problem select genes with correlation techniques. We propose a new method of gene selection utilizing Support Vector Machine methods

, and stratiÞed squamous epithelium (ectoderm). These cell lines should be useful in human develop-mental biology, drug discovery, and transplantation medicine. Embryonic stem (ES) cells are derived from totipotent cells of the early mamma-lian embryo and are capable of unlimited, undifferentiated proliferation

for the discovery of frequent itemsets, which forms the compute intensive phase of the task. The algorithms utilize the structural properties of frequent itemsets to facilitate fast discovery. The related database items are grouped together into clusters representing the potential maximal frequent itemsets

for the discovery of frequent itemsets, which forms the compute intensive phase of the task. The algorithms utilize the structural properties of frequent itemsets to facilitate fast discovery. The items are organized into a subset lattice search space, which is decomposed into small independent chunks or sub

Abstract Signal finding (pattern discovery in unaligned DNA sequences) is a fundamental problem in both computer science and molecular biology with important applications in locating regulatory sites and drug target identification. Despite many studies, this problem is far from being resolved

to the comparison group from reduced disease transmission, and therefore also underestimating benefits for the treatment group. We evaluate a Kenyan project in which school-based mass treatment with deworming drugs was randomly phased into schools, rather than to individuals, allowing estimation of overall program

A higher order recurrent neural network architecture learns to recognize and generate languages after being "trained " on categorized exemplars. Studying these networks from the perspective of dynamical systems yields two interesting discoveries: First, a longitudinal examination

and utility across a wide range of chemical biology and drug-discovery research problems. Currently, the database contains 5.4 million bioactivity meas-urements for more than 1 million compounds and 5200 protein targets. Access is available through a web-based interface, data downloads and web ser-vices at:

minimized structures, with a root-mean-square displacement of 0.26 Å, which is comparable to that of the Tripos 5.2 force field (0.25 Å) and better than those of MMFF 94 and CHARMm (0.47 and 0.44 Å, respectively). In test II, gas phase minimizations were performed on 22 nucleic acid base pairs