Search results for "quantitative"
showing 10 items of 2409 documents
Extinct type of human parvovirus B19 persists in tonsillar B cells
2017
Parvovirus B19 (B19V) DNA persists lifelong in human tissues, but the cell type harbouring it remains unclear. We here explore B19V DNA distribution in B, T and monocyte cell lineages of recently excised tonsillar tissues from 77 individuals with an age range of 2–69 years. We show that B19V DNA is most frequent and abundant among B cells, and within them we find a B19V genotype that vanished from circulation >40 years ago. Since re-infection or re-activation are unlikely with this virus type, this finding supports the maintenance of pathogen-specific humoral immune responses as a consequence of B-cell long-term survival rather than continuous replenishment of the memory pool. Moreover, we …
Fragments of peer review: A quantitative analysis of the literature (1969-2015)
2018
This paper examines research on peer review between 1969 and 2015 by looking at records indexed from the Scopus database. Although it is often argued that peer review has been poorly investigated, we found that the number of publications in this field doubled from 2005. A half of this work was indexed as research articles, a third as editorial notes and literature reviews and the rest were book chapters or letters. We identified the most prolific and influential scholars, the most cited publications and the most important journals in the field. Co-authorship network analysis showed that research on peer review is fragmented, with the largest group of co-authors including only 2.1% of the wh…
Retrieving infinite numbers of patterns in a spin-glass model of immune networks
2013
The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…
Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony
2016
In this paper, we study neuronal network analysis based on microelectrode measurements. We search for potential relations between time correlated changes in spectral distributions and synchrony for neuronal network activity. Spectral distribution is quantified by spectral entropy as a measure of uniformity/complexity and this measure is calculated as a function of time for the recorded neuronal signals, i.e., time variant spectral entropy. Time variant correlations in the spectral distributions between different parts of a neuronal network, i.e., of concurrent measurements via different microelectrodes, are calculated to express the relation with a single scalar. We demonstrate these relati…
Multiple steady states and the form of response functions to antigen in a model for the initiation of T cell activation
2017
The aim of this paper is to study the qualitative behaviour predicted by a mathematical model for the initial stage of T-cell activation. The state variables in the model are the concentrations of phosphorylation states of the T-cell receptor (TCR) complex and the phosphatase SHP-1 in the cell. It is shown that these quantities cannot approach zero and that the model possesses more than one positive steady state for certain values of the parameters. It can also exhibit damped oscillations. It is proved that the chemical concentration which represents the degree of activation of the cell, that of the maximally phosphorylated form of the TCR complex, is, in general, a non-monotone function of…
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 …
A generalization of Kingman's model of selection and mutation and the Lenski experiment.
2017
Kingman’s model of selection and mutation studies the limit type value distribution in an asexual population of discrete generations and infinite size undergoing selection and mutation. This paper generalizes the model to analyze the long-term evolution of Escherichia. coli in Lenski experiment. Weak assumptions for fitness functions are proposed and the mutation mechanism is the same as in Kingman’s model. General macroscopic epistasis are designable through fitness functions. Convergence to the unique limit type distribution is obtained.
panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data.
2018
Abstract Motivation The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data. Results PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic spec…
Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.
2017
International audience; Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algori…
LEGO-based generalized set of two linear algebraic 3D bio-macro-molecular descriptors: Theory and validation by QSARs
2019
Abstract Novel 3D protein descriptors based on bilinear, quadratic and linear algebraic maps in R n are proposed. The latter employs the kth 2-tuple (dis) similarity matrix to codify information related to covalent and non-covalent interactions in these biopolymers. The calculation of the inter-amino acid distances is generalized by using several dis-similarity coefficients, where normalization procedures based on the simple stochastic and mutual probability schemes are applied. A new local-fragment approach based on amino acid-types and amino acid-groups is proposed to characterize regions of interest in proteins. Topological and geometric macromolecular cutoffs are defined using local and…