BACKGROUND: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. RESULTS: We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. CONCLUSIONS: This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups.

A PC based desktop Virtual Reality system was developed for rehabilitating hand function in stroke patients. The system uses two hand input devices, a CyberGlove and a RMII force feedback glove, to allow the user to interact with one of four rehabilitation exercises. Each of which is designed to exercise one specific parameter of hand movement, namely range, speed, fractionation or strength. The therapy program is semi-automated and personalized to each user through the use of performance-based target levels. These are adapted between sessions in order to induce the user to improve. Feedback is provided to each user throughout the exercise sessions. To further motivate the user to continue the exercise program, screen displays are designed as interactive games. The system is described and sample data is presented from preliminary studies performed on control subjects.

A genetic algorithm is used to search for the rhythmical control of eight joints in a quadruped robot. The search is used to find a fixed number of Fourier coefficients for each joint. Each set of coefficients is considered to be a controller for the robot, and it is evaluated using a simulator of the dynamics of the walking pattern generated by the controller. The fitness of a controller is higher if it generates more stable and faster walking. Effective controllers are further evaluated using a purpose-built robot that is physically modeled in the simulator. We present initial results from this simulation system, and show good correspondence between the simulator-generated dynamics and the movement of the robot under control of the same set of coefficients. The results presented here suggest that stable limit cycles may exist in the dynamics of quadruped walking.