Search results for "recognition"
showing 10 items of 3607 documents
Variable Ranking Feature Selection for the Identification of Nucleosome Related Sequences
2018
Several recent works have shown that K-mer sequence representation of a DNA sequence can be used for classification or identification of nucleosome positioning related sequences. This representation can be computationally expensive when k grows, making the complexity in spaces of exponential dimension. This issue effects significantly the classification task computed by a general machine learning algorithm used for the purpose of sequence classification. In this paper, we investigate the advantage offered by the so-called Variable Ranking Feature Selection method to select the most informative k − mers associated to a set of DNA sequences, for the final purpose of nucleosome/linker classifi…
Clustering of low-correlated spatial gene expression patterns in the mouse brain in the Allen Brain Atlas
2018
In this paper, clustering techniques are applied to spatial gene expression patterns with a low genomic correlation between the sagittal and coronal projections. The data analysed here are hosted on an available public DB named ABA (Allen Brain Atlas). The results are compared to those obtained by Bohland et al. on the complementary dataset (high correlation values). We prove that, by analysing a reduced dataset,hence reducing the computational burden, we get the same accuracy in highlighting different neuroanatomical region.
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…
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…
The intrinsic combinatorial organization and information theoretic content of a sequence are correlated to the DNA encoded nucleosome organization of…
2015
Abstract Motivation: Thanks to research spanning nearly 30 years, two major models have emerged that account for nucleosome organization in chromatin: statistical and sequence specific. The first is based on elegant, easy to compute, closed-form mathematical formulas that make no assumptions of the physical and chemical properties of the underlying DNA sequence. Moreover, they need no training on the data for their computation. The latter is based on some sequence regularities but, as opposed to the statistical model, it lacks the same type of closed-form formulas that, in this case, should be based on the DNA sequence only. Results: We contribute to close this important methodological gap …
In vitro versus in vivo compositional landscapes of histone sequence preferences in eucaryotic genomes
2018
Abstract Motivation Although the nucleosome occupancy along a genome can be in part predicted by in vitro experiments, it has been recently observed that the chromatin organization presents important differences in vitro with respect to in vivo. Such differences mainly regard the hierarchical and regular structures of the nucleosome fiber, whose existence has long been assumed, and in part also observed in vitro, but that does not apparently occur in vivo. It is also well known that the DNA sequence has a role in determining the nucleosome occupancy. Therefore, an important issue is to understand if, and to what extent, the structural differences in the chromatin organization between in vit…
DNA structure-specific sensitization of a metalloporphyrin leads to an efficient in vitro quadruplex detection molecular tool
2016
International audience; The search for convenient molecular probes for detecting DNA and RNA quadruplexes in vitro is marked by a rapid pace of progress, spurred on by the multiple roles these higher-order nucleic acid structures play in many genetic dysregulations. Here, we contribute to this search, reporting on a palladated porphyrin named Pd.TEGPy: its efficiency as quadruplex-selective fluorescent dye relies on a structural design that endows it with attractive supramolecular and electronic properties and makes it an efficient turn-on, quadruplex-selective fluorescent stain thanks to a DNA-mediated sensitization mechanism that ensures a high level of specificity.
Deep learning models for bacteria taxonomic classification of metagenomic data.
2018
Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…
Anti-inflammatory and cognitive effects of interferon-β1a (IFNβ1a) in a rat model of Alzheimer’s disease
2018
Background: Aβ 1-42 peptide abnormal production is associated with the development and maintenance of neuroinflammation and oxidative stress in brains from Alzheimer disease (AD) patients. Suppression of neuroinflammation may then represent a suitable therapeutic target in AD. We evaluated the efficacy of IFNβ1a in attenuating cognitive impairment and inflammation in an animal model of AD. Methods: A rat model of AD was obtained by intra-hippocampal injection of Aβ 1-42 peptide (23 μg/2 μl). After 6 days, 3.6 μg of IFNβ1a was given subcutaneously (s.c.) for 12 days. Using the novel object recognition (NOR) test, we evaluated changes in cognitive function. Measurement of pro-inflammatory or …
Evolutionary redesign of the Atlantic cod (Gadus morhua L.) Toll-like receptor repertoire by gene losses and expansions
2016
AbstractGenome sequencing of the teleost Atlantic cod demonstrated loss of the Major Histocompatibility Complex (MHC) class II, an extreme gene expansion of MHC class I and gene expansions and losses in the innate pattern recognition receptor (PRR) family of Toll-like receptors (TLR). In a comparative genomic setting, using an improved version of the genome, we characterize PRRs in Atlantic cod with emphasis on TLRs demonstrating the loss of TLR1/6, TLR2 and TLR5 and expansion of TLR7, TLR8, TLR9, TLR22 and TLR25. We find that Atlantic cod TLR expansions are strongly influenced by diversifying selection likely to increase the detectable ligand repertoire through neo- and subfunctionalizatio…