Differential Network Analysis of Anti-sense Regulation

A challenging task in systems biology is to decipher cell regulation mechanisms. By comparing networks observed in two different situations, the differential network analysis approach enables to highlight interaction differences that reveal specific cellular responses. The aim of our work is to study the role of natural anti-sense transcription on cellular regulation mechanisms. Our proposal is to build and compare networks obtained from two different sets of actors: the “usual” sense actors on one hand and the sense and anti-sense actors on the other hand. Our study only considers the most significant interactions, called an Extended Core Network; therefore our differential analysis identifies important interactions that are impacted by anti-sense transcription. This paper first introduces our inference method of an Extended Core Network; this method is inspired by C3NET, but whereas C3NET only computes one interaction per gene, we propose to consider the most significant interactions for each gene. Secondly, we define the differential network analysis of two extended core networks inferred with and without anti-sense actors. On a local view, this analysis relies on change motifs that describe which genes have their most important interactions modified when the anti-sense transcripts are considered; they are called AS-impacted genes. Then from a more global view, we consider how the relationships between these AS-impacted genes are rewired in the network with anti-sense actors. Our analysis is performed by computing Steiner trees that represent minimal subnetworks connecting the AS-impacted genes. We show that the visualisation of these results help the biologists to identify interesting parts of the networks

Inference and Differential Analysis of Extended Core Networks: a way to study Anti-Sense Regulation

A key issue in bioinformatics is to decipher cell regulation mechanisms. By comparing networks observed in two different situations, differential network analysis enables to highlight differences that reveal specific cellular responses. The aim of our work is to study the role of natural anti-sense transcription on cellular regulation mechanisms. Our proposal is to build and compare networks obtained from two different sets of actors: the “usual” sense actors on one hand and the sense and anti-sense actors on the other hand. Our study only considers themost significant interactions, called an Extended Core Network; therefore our differential analysis identifies important interactions that are on the influence of anti-sense transcription. Our inference method of an Extended Core Network is inspired by C3NET, but whereas C3NET only computes one interaction per gene, we propose to consider the most significant interactions for each gene. We define the differential network analysis of two extended core networks inferred with and without anti-sense actors. This relies on change motifs that describe which gene-gene interactions of the extended core network are modified when we integrate anti-sense actors in the data. As our method ocuses on the most significant interactions, these motifs highlight the impact of anti-sense transcription. The networks motifs obtained by our workflow are then compared with assessed biological knowledge. The study reported in this paper is realized on transcriptional data from apple fruit in a context of fruit ripening; the change motifs revealed by our analysis are matched on a protein-protein interaction network and give a small set of interesting actors thatdeserve further biological investigation

Differential Functional Analysis and Change Motifs in Gene Networks to Explore the Role of Anti-sense Transcription

Several transcriptomic studies have shown the widespread existence of anti-sense transcription in cell. Anti-sense RNAs may be important actors in transcriptional control, especially in stress response processes. The aim of our work is to study gene networks, with the particularity to integrate in the process anti-sense transcripts. In this paper, we first present a method that highlights the importance of taking into account anti-sense data into functional enrichment analysis. Secondly, we propose the differential analysis of gene networks built with and without anti-sense actors in order to discover interesting change motifs that involve the anti-sense transcripts. For more reliability, our network comparison only studies the conservative causal part of a network, inferred by the C3NET method. Our work is realized on transcriptomic data from apple fruit

A Graphical Language to Query Conceptual Graphs

This paper presents a general query language for conceptual graphs. First, we introduce kernel query graphs. A kernel query graph can be used to express an "or" between two sub-graphs, or an "option" on an optional sub-graph. Second, we propose a way to express two kinds of queries (ask and select) using kernel query graphs. Third, the answers of queries are computed by an operation based on graph homomorphism: the projection from a kernel query graph

Comparaison de réseaux de gènes pour explorer le rôle des transcrits anti-sens

Un des problèmes clés en bioinformatique est de comprendre les mé- canismes de régulation au sein d’une cellule. Notre travail concerne l’étude des réseaux de gènes chez le pommier, avec la particularité d’y intégrer les acteurs encore mal connus que sont les ARN anti-sens. Pour explorer l’impact des trans- crits anti-sens, nous proposons ici la comparaison des deux réseaux obtenus par une méthode d’inférence très conservative. Nous pouvons ainsi étudier les in- teractions directes entre les gènes qui sont modifiées si l’on fait intervenir les transcrits anti-sens dans la méthode d’inférence. Un ensemble de motifs caracté- ristiques autour de ces modifications permet de révéler des ensembles d’acteurs sens et anti-sens intéressants

Estimation of roads longitudinal roughness using longitudinal profile analysor signal filtering

Experts of roads and public works have been interested for a long time in the bumps on the road ways . Such road defects with regard to a flat surface, are called the roughness of the road . The longitudinal profile analysor (LPA) was made by the « Laboratoire Central des Pants et Chaussées » in Nantes, in order to measure the roughness . The signal given by this plant can be considered as the output of a linear system whose input is the unknown longitudinal section of the road . We present in this paper two methods for solving this problem : the first one is determinist and uses a back filtering by the transfer function of the LPA. The second one is stochastic and uses Kalman filtering . At first, we modelize the LPA by a fifth order transfert function built with a description of its differents mechanic and electronic components and by an experimental frequency analysis . Then the double filtering technic eliminates the phase distortions of the LPA signal, so we obtain a pseudo profile reproduicing the exact profile with an attenuation for frequencies outside the analysor band pass . The second method uses a LPA model obtained by parametric identification (maximum likelihood method) and a model of the profile type Wiener signal . Then we implement an optimal Kalman filter. After eliminating polynomial components and low frequencies, the reconstructed signal follows accurately variations of the roughness road . Results obtained from measurements made on a test bed and an experimental way are presented .Les spécialistes du monde routier et des travaux public s'intéressent depuis longtemps aux aspérités présentes sur les chaussées. Ces défauts de la route par rapport à une surface idéalement plane constituent ce que l'on appelle son uni. L'analyseur de profil en long, l'APL, a été conçu par le Laboratoire Central des Ponts et Chaussées de Nantes afin de mesurer cet uni. Le signal que délivre cet appareil peut être considéré comme la sortie d'un système linéaire dont l'entrée est le profil inconnu de la route. Le signal que délivre cet appareil peut être considéré comme la sortie d'un système linéaire dont l'entrée est le profil de la route. L'image qu'il donne des défauts de la chaussée est déformée par rapport à la forme réelle de ces défauts, les utilisateurs sont demandeurs d'une estimation plus précise de ceux- ci. Il se pose donc le problème de la déconvolution du signal APL. Pour résoudre ce problème, on propose dans ce papier, deux approches, l'une déterministe utilisant un filtrage retour par la fonction de transfert de l'APL, l'autre stochastique par filtrage de Kalman. Dans un premier temps on modélise l'APL par une fonction de transfert du Sème ordre construite à partir d'une description des différents organes mécaniques et électroniques qui le constituent et d'une analyse harmonique expérimentale. La technique du double filtrage permet alors d'éliminer les distorsions de phases du signal APL et d'obtenir ainsi un pseudo profil qui ne diffère du profil exact que par des atténuations pour des fréquences extérieures à la bonde passante de l'analyseur. La deuxième approche utilise un modèle de l'APL obtenu par identification paramétrique (méthode du maximum de vraisemblance) et un modèle du profil du type signal de Wiener. On met alors en oeuvre un filtre estimateur optimal stationnaire de Kalman. Après élimination des composantes polynomiales et basses fréquences le signal reconstruit suit fidèlement les variations de l'uni de la chaussée. Des résultats, obtenus à partir d'enregistrements effectués au banc d'essais et sur une piste expérimentale, sont présentés

Extended-spectrum β-lactamase Enterobacteriaceae (ESBLE) in intensive care units: strong correlation with the ESBLE colonization pressure in patients but not same species

Sink drains of six intensive care units (ICUs) were sampled for screening contamination with extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBLE). A high prevalence (59.4%) of sink drain contamination was observed. Analysing the data by ICU, the ratio \u27number of ESBLE species isolated in sink drains/total number of sink drains sampled\u27 was highly correlated (Spearman coefficient: 0.87; P = 0.02) with the ratio \u27number of hospitalization days for patients with ESBLE carriage identified within the preceding year/total number of hospitalization days within the preceding year\u27. Concurrently, the distribution of ESBLE species differed significantly between patients and sink drains