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Cytometry is an experimental technique used to measure molecules expressed by cells at a single cell resolution. Recently, several technological improvements have made possible to increase greatly the number of cell markers that can be simultaneously measured. Many computational methods have been proposed to identify clusters of cells having similar phenotypes. Nevertheless, only a limited number...
Biological processes often manifest themselves as coordinated changes across modules, i.e., sets of interacting genes. Commonly, the high dimensionality of genome-scale data prevents the visual identification of such modules, and straightforward computational search through a set of known pathways is a limited approach. Therefore, tools for the data-driven, computational, identification of modules...
This paper presents several geometrically motivated techniques for the visualization of high-dimensional biological data sets. The Grassmann manifold provides a robust framework for measuring data similarity in a subspace context. Sparse radial basis function classification as a visualization technique leverages recent advances in radial basis function learning via convex optimization. In the spirit...
Life sciences are currently going through a great number of transformations raised by the in-going revolution in high-throughput technologies for the acquisition of data. The integration of their high dimensionality, ranging from omics to clinical data, is becoming one of the most challenging stages. It involves inter-disciplinary developments with the aim to move towards an enhanced understanding...
Toxicity affecting humans is studied by observing the effects of chemical substances in animal organisms (in vivo) or in animal and human cultivated cell lines (in vitro). Toxicogenomics studies collect gene expression profiles and histopathology assessment data for hundreds of drugs and pollutants in standardized experimental designs using different model systems. These data are an invaluable source...
Can we use graph mining algorithms to find patterns in tumor molecular mechanisms? Can we model disease progression with multiple time-specific graph comparison algorithms? In this paper, we will focus on this area. Our main contributions are 1) we proposed the Temporal-Omics (Temp-O) workflow to model tumor progression in non-small cell lung cancer (NSCLC) using graph comparisons between multiple...
Biological sequences can be considered as data items of high-, non-fixed dimensions, corresponding to the length of those sequences. The comparison and the classification of biological sequences in their relations to large databases are important areas of research today. Artificial neural networks (ANNs) have gained a well-deserved popularity among machine learning tools upon their recent successful...
RNA-Seq is becoming the standard technology for large-scale gene expression level measurements, as it offers a number of advantages over microarrays. Standards for RNA-Seq data analysis are, however, in its infancy when compared to those of microarrays. Clustering, which is essential for understanding gene expression data, has been widely investigated w.r.t. microarrays. In what concerns the clustering...
Currently, there is no widely accepted technique to efficiently and reproducibly grow stem and progenitor cells in vitro. Stem cells require contact with extracellular matrices as well as signals from growth factors to proliferate and to retain their stemness. We have shown a novel tissue culture platform (StemTrix cultureware) that transforms standard tissue culture plasticware into a multi-functional...
Neural progenitor cells hold significant promise in a variety of clinical settings. While both the brain and spinal cord harbor endogenous neural progenitor or stem cells, they typically are not capable of repopulating neural populations in case of injury or degenerative disease. In vitro systems for the culture of neural progenitors has come a long ways due to advances in the method development....
Neural stem cell (NSC) cultures have been considered technically challenging for time-lapse analysis due to high motility, photosensitivity, and growth at confluent densities. We have tested feasibility of long-term live-cell time-lapse analysis for NSC migration and differentiation studies. Here, we describe a method to study the dynamics of cell cycle, migration, and lineage selection in cultured...
The neural crest (NC) is a transient embryonic cell population with remarkable characteristics. After delaminating from the neural tube, NC cells (NCCs) migrate extensively, populate nearly every tissue of the body and differentiate into highly diverse cell types such as peripheral neurons and glia, but also mesenchymal cells including chondrocytes, osteocytes, and adipocytes. While the NC has been...
Whole cell membrane capacitance is an electrophysiological property of the plasma membrane that serves as a biomarker for stem cell fate potential. Neural stem and progenitor cells (NSPCs) that differ in ability to form neurons or astrocytes are distinguished by membrane capacitance measured by dielectrophoresis (DEP). Differences in membrane capacitance are sufficient to enable the enrichment of...
Research on the biology of adult neural stem cells (NSCs) and induced NSCs (iNSCs), as well as NSC-based therapies for diseases in central nervous system (CNS) has started to generate the expectation that these cells may be used for treatments in CNS injuries or disorders. Recent technological progresses in both NSCs themselves and their derivatives have brought us closer to therapeutic applications...
Therapeutic approaches based on stem cells have received considerable attention as potential treatments for Huntington’s disease (HD), which is a fatal, inherited neurodegenerative disorder, caused by progressive loss of GABAergic medium spiny neurons (MSNs) in the striatum of the forebrain. Transplantation of stem cells or their derivatives in animal models of HD, efficiently improved functions by...
Proteins are drivers of cell functions and are targets of many therapies. Exogenous protein expression techniques, therefore, have been essential for research and medicine. The most common method for exogenous protein expression relies on DNA-based viral or non-viral vectors. However, DNA-based vectors have the potential to integrate into the host genome and cause permanent mutations. RNA-based vectors...
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