Search results for "dolo"
showing 10 items of 4274 documents
Response to I. Batinic-Haberle et al.
2016
Letter to the editor.-- et al.
View images with unprecedented resolution in integral microscopy
2018
Integral microscopy is a novel technique that allows the simultaneous capture of multiple perspective images of microscopic samples. This feature is achieved at the cost of a significant reduction of the spatial resolution. In fact, it is assumed that in the best cases the resolution is reduced by a factor that is not smaller than ten, what poses a hard drawback to the utility of the technique. However, to the best of our knowledge, this resolution limitation has never been researched rigorously. For this reason, the aim of this paper is to explore the real limitations in resolution of integral microscopy and to obtain optically, without the need of any image-processing algorithm, perspecti…
Automated selection of homologs to track the evolutionary history of proteins
2018
Background The selection of distant homologs of a query protein under study is a usual and useful application of protein sequence databases. Such sets of homologs are often applied to investigate the function of a protein and the degree to which experimental results can be transferred from one organism to another. In particular, a variety of databases facilitates static browsing for orthologs. However, these resources have a limited power when identifying orthologs between taxonomically distant species. In addition, in some situations, for a given query protein, it is advantageous to compare the sets of orthologs from different specific organisms: this recursive step-wise search might give …
A novel D2O tracer method to quantify RNA turnover as a biomarker of de novo ribosomal biogenesis, in vitro, in animal models, and in human skeletal …
2017
Current methods to quantify in vivo RNA dynamics are limited. Here, we developed a novel stable isotope (D2O) methodology to quantify RNA synthesis (i.e., ribosomal biogenesis) in cells, animal models, and humans. First, proliferating C2C12 cells were incubated in D2O-enriched media and myotubes ±50 ng/ml IGF-I. Second, rat quadriceps (untrained, n = 9; 7-wk interval-“like” training, n = 13) were collected after ~3-wk D2O (70 atom %) administration, with body-water enrichment monitored via blood sampling. Finally, 10 (23 ± 1 yr) men consumed 150-ml D2O followed by 50 ml/wk and undertook 6-wk resistance exercise (6 × 8 repetitions, 75% 1-repetition maximum 3/wk) with body-water enrichment mo…
Carbon based nanomaterials for tissue engineering of bone: Building new bone on small black scaffolds: A review.
2019
Graphical abstract
Discovering discriminative graph patterns from gene expression data
2016
We consider the problem of mining gene expression data in order to single out interesting features characterizing healthy/unhealthy samples of an input dataset. We present an approach based on a network model of the input gene expression data, where there is a labelled graph for each sample. To the best of our knowledge, this is the first attempt to build a different graph for each sample and, then, to have a database of graphs for representing a sample set. Our main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminative patterns" among graphs belonging to the two different sample sets. Differently from the other…
Imaging through scattering media by microstructured illumination
2016
We describe a method to image objects through scattering media based on microstructured illumination. A spatial light modulator is used to project a set of microstructured light patterns onto the sample. The image is retrieved computationally from the photocurrent fluctuations provided by a detector with no spatial structure. We review several optical setups developed in the last years with different illumination strategies and applied to different turbid media. In particular we introduce a new non-invasive optical system based on a reflection configuration. Our technique does not require coherent light, raster scanning, time-gated detection or a-priori calibration processes. Furthermore it…
Partitioned learning of deep Boltzmann machines for SNP data.
2016
Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…
Gene-based and semantic structure of the Gene Ontology as a complex network
2012
The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. This approach might be usefully complemented by a bottom-up approach based on the knowledge of relationships amongst genes. To this end, we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium and a gene-based …
L1-Penalized Censored Gaussian Graphical Model
2018
Graphical lasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. Typical examples are data generated by polymerase chain reactions and flow cytometer. The combination of censoring and high-dimensionality make inference of the underlying genetic networks from these data very challenging. In this article, we propose an $\ell_1$-penalized Gaussian graphical model for censored data and derive two EM-like algorithm…