Novel visualization methods for protein data

Visualization of high-dimensional data has always been a challenging task. Here we discuss and propose variants of non-linear data projection methods (Generative Topographic Mapping (GTM) and GTM with simultaneous feature saliency (GTM-FS)) that are adapted to be effective on very high-dimensional data. The adaptations use log space values at certain steps of the Expectation Maximization (EM) algorithm and during the visualization process. We have tested the proposed algorithms by visualizing electrostatic potential data for Major Histocompatibility Complex (MHC) class-I proteins. The experiments show that the variation in the original version of GTM and GTM-FS worked successfully with data of more than 2000 dimensions and we compare the results with other linear/nonlinear projection methods: Principal Component Analysis (PCA), Neuroscale (NSC) and Gaussian Process Latent Variable Model (GPLVM).

Microspheres as a vehicle for biomolecule delivery to neural stem cells

Neural stem cells (NSC) are a valuable model system for understanding the intrinsic and extrinsic controls for self-renewal and differentiation choice. They also offer a platform for drug screening and neurotoxicity studies, and hold promise for cell replacement therapies for the treatment of neurodegenerative diseases. Fully exploiting the potential of this experimental tool often requires the manipulation of intrinsic cues of interest using transfection methods, to which NSC are relatively resistant. In this paper, we show that mouse and human NSC readily take up polystyrene-based microspheres which can be loaded with a range of chemical or biological cargoes. This uptake can take place in the undifferentiated stage without affecting NSC proliferation and their capacity to give rise to neurons and glia. We demonstrate that ß-galactosidase-loaded microspheres could be efficiently introduced into NSC with no apparent toxic effect, thus providing proof-of-concept for the use of microspheres as an alternative biomolecule delivery system.