Search results for "Probability."
showing 10 items of 3396 documents
Nature lessons: the whitefly bacterial endosymbiont is a minimal amino acid factory with unusual energetics
2016
Reductive genome evolution is a universal phenomenon observed in endosymbiotic bacteria in insects. As the genome reduces its size and irreversibly losses coding genes, the functionalities of the cell system, including the energetics processes, are more restricted. Several energetic pathways can also be lost. How do these reduced metabolic networks sustain the energy needs of the system? Among the bacteria with reduced genomes Candidatus Portiera aleyrodidarum, obligate endosymbiont of whiteflies, represents an extreme case since lacks several key mechanisms for ATP generation. Thus, to analyze the cell energetics in this system, a genome-scale metabolic model of this endosymbiont was const…
The latent geometry of the human protein interaction network
2017
Abstract Motivation A series of recently introduced algorithms and models advocates for the existence of a hyperbolic geometry underlying the network representation of complex systems. Since the human protein interaction network (hPIN) has a complex architecture, we hypothesized that uncovering its latent geometry could ease challenging problems in systems biology, translating them into measuring distances between proteins. Results We embedded the hPIN to hyperbolic space and found that the inferred coordinates of nodes capture biologically relevant features, like protein age, function and cellular localization. This means that the representation of the hPIN in the two-dimensional hyperboli…
A deterministic model for highly contagious diseases: The case of varicella
2016
[EN] The classic nonlinear Kermack-McKendrick model based upon a system of differential equations has been widely applied to model the rise and fall of global pandemic and also seasonal epidemic by introducing a forced harmonic infectivity which would change throughout the year. These methods work well in their respective domains of applicability, and for certain diseases, but they fail when both seasonality and high infectivity are combined. In this paper we consider a Susceptible-Infected-Recovered, or SIR, model with two latent states to model the propagation and evolutionary history of varicella in humans. We show that infectivity can be calculated from real data and we find a nonstanda…
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…
Mathematical investigation of innate immune responses to lung cancer: The role of macrophages with mixed phenotypes
2021
Abstract Macrophages’ role in the evolution of solid tumours is a well accepted fact, with the M1-like macrophages having an anti-tumour role and the M2-like macrophages having a pro-tumour role. Despite the fact that some clinical studies on lung tumours have emphasised also the presence of macrophages with mixed M1 and M2 phenotypes in addition to macrophages with distinct phenotypes, the majority of studies still use the distinct M1-M2 classification to predict the evolution of tumours and patient survival. In this theoretical study we use a mathematical modelling and computational approach to investigate the role of macrophages with mixed phenotype on growth/control/elimination of lung …
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…
A heuristic, iterative algorithm for change-point detection in abrupt change models
2017
Change-point detection in abrupt change models is a very challenging research topic in many fields of both methodological and applied Statistics. Due to strong irregularities, discontinuity and non-smootheness, likelihood based procedures are awkward; for instance, usual optimization methods do not work, and grid search algorithms represent the most used approach for estimation. In this paper a heuristic, iterative algorithm for approximate maximum likelihood estimation is introduced for change-point detection in piecewise constant regression models. The algorithm is based on iterative fitting of simple linear models, and appears to extend easily to more general frameworks, such as models i…
A graphical model selection tool for mixed models
2017
Model selection can be defined as the task of estimating the performance of different models in order to choose the most parsimonious one, among a potentially very large set of candidate statistical models. We propose a graphical representation to be considered as an extension to the class of mixed models of the deviance plot proposed in the literature within the framework of classical and generalized linear models. This graphical representation allows, once a reduced number of models have been selected, to identify important covariates focusing only on the fixed effects component, assuming the random part properly specified. Nevertheless, we suggest also a standalone figure representing th…
Reverse screening on indicaxanthin from Opuntia ficus-indica as natural chemoactive and chemopreventive agent
2018
Indicaxanthin is a bioactive and bioavailable betalain pigment extracted from Opuntia ficus indica fruits. Indicaxanthin has pharmacokinetic proprieties, rarely found in other phytochemicals, and it has been demonstrated that it provides a broad-spectrum of pharmaceutical activity, exerting anti-proliferative, anti-inflammatory, and neuromodulator effects. The discovery of the Indicaxanthin physiological targets plays an important role in understanding the biochemical mechanism. In this study, combined reverse pharmacophore mapping, reverse docking, and text-based database search identified Inositol Trisphosphate 3-Kinase (ITP3K-A), Glutamate carboxypeptidase II (GCPII), Leukotriene-A4 hydr…
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…