Explanations and Proof Trees

This paper proposes a model for explanations in a set theoretical framework using the notions of closure or fixpoint. In this approach, sets of rules associated with monotonic operators allow to define proof trees. The proof trees may be considered as a declarative view of the trace of a computation. We claim they are explanations of the results of a computation. This notion of explanation is applied to constraint logic programming, and it is used for declarative error diagnosis. It is also applied to constraint programming, and used for constraint retraction

Evolutionary Latent Class Clustering of Qualitative Data

The latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous populations. It uses a conditional independence assumption given the latent class to which a statistical unit is belonging. However, whereas a predictive approach of cluster analysis from qualitative data can be easily derived from a fully Bayesian analysis with Jeffreys non informative prior distributions, it leads to a criterion (the integrated completed likelihood derived from the latent class model) that proves difficult to optimize by the standard approach based on the EM algorithm. An Evolutionary Algorithms is designed to tackle this discrete optimization problem, and an extensive parameter study on a large artificial dataset allows to derive stable parameters. A Monte Carlo approach is used to validate those parameters on other artificial datasets, as well as on some well-known real data: the Evolutionary Algorithm seems to repeatedly perform better than other standard clustering techniques on the same data

Parameter Setting for Evolutionary Latent Class Clustering

International audienceThe latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous populations. It uses a conditional independence assumption given the latent class to which a statistical unit is belonging. However, it leads to a criterion that proves difficult to optimise by the standard approach based on the EM algorithm. An Evolutionary Algorithms is designed to tackle this discrete optimisation problem, and an extensive parameter study on a large artificial dataset allows to derive stable parameters. Those parameters are then validated on other artificial datasets, as well as on some well-known real data: the Evolutionary Algorithm performs repeatedly better than other standard clustering techniques on the same data

wDBTF: an integrated database resource for studying wheat transcription factor families

<p>Abstract</p> <p>Background</p> <p>Transcription factors (TFs) regulate gene expression by interacting with promoters of their target genes and are classified into families based on their DNA-binding domains. Genes coding for TFs have been identified in the sequences of model plant genomes. The rice (<it>Oryza sativa </it>spp. <it>japonica</it>) genome contains 2,384 TF gene models, which represent the mRNA transcript of a locus, classed into 63 families.</p> <p>Results</p> <p>We have created an extensive list of wheat (<it>Triticum aestivum </it>L) TF sequences based on sequence homology with rice TFs identified and classified in the Database of Rice Transcription Factors (DRTF). We have identified 7,112 wheat sequences (contigs and singletons) from a dataset of 1,033,960 expressed sequence tag and mRNA (ET) sequences available. This number is about three times the number of TFs in rice so proportionally is very similar if allowance is made for the hexaploidy of wheat. Of these sequences 3,820 encode gene products with a DNA-binding domain and thus were confirmed as potential regulators. These 3,820 sequences were classified into 40 families and 84 subfamilies and some members defined orphan families. The results were compiled in the Database of Wheat Transcription Factor (wDBTF), an inventory available on the web <url>http://wwwappli.nantes.inra.fr:8180/wDBFT/</url>. For each accession, a link to its library source and its Affymetrix identification number is provided. The positions of Pfam (protein family database) motifs were given when known.</p> <p>Conclusions</p> <p>wDBTF collates 3,820 wheat TF sequences validated by the presence of a DNA-binding domain out of 7,112 potential TF sequences identified from publicly available gene expression data. We also incorporated <it>in silico </it>expression data on these TFs into the database. Thus this database provides a major resource for systematic studies of TF families and their expression in wheat as illustrated here in a study of DOF family members expressed during seed development.</p

Evolutionary Latent Class Clustering of Qualitative Data

The latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous populations. It uses a conditional independence assumption given the latent class to which a statistical unit is belonging. However, whereas a predictive approach of cluster analysis from qualitative data can be easily derived from a fully Bayesian analysis with Jeffreys non informative prior distributions, it leads to a criterion (the integrated completed likelihood derived from the latent class model) that proves difficult to optimize by the standard approach based on the EM algorithm. An Evolutionary Algorithms is designed to tackle this discrete optimization problem, and an extensive parameter study on a large artificial dataset allows to derive stable parameters. A Monte Carlo approach is used to validate those parameters on other artificial datasets, as well as on some well-known real data: the Evolutionary Algorithm seems to repeatedly perform better than other standard clustering techniques on the same data

The Homeodomain Derived Peptide Penetratin Induces Curvature of Fluid Membrane Domains

BACKGROUND:Protein membrane transduction domains that are able to cross the plasma membrane are present in several transcription factors, such as the homeodomain proteins and the viral proteins such as Tat of HIV-1. Their discovery resulted in both new concepts on the cell communication during development, and the conception of cell penetrating peptide vectors for internalisation of active molecules into cells. A promising cell penetrating peptide is Penetratin, which crosses the cell membranes by a receptor and metabolic energy-independent mechanism. Recent works have claimed that Penetratin and similar peptides are internalized by endocytosis, but other endocytosis-independent mechanisms have been proposed. Endosomes or plasma membranes crossing mechanisms are not well understood. Previously, we have shown that basic peptides induce membrane invaginations suggesting a new mechanism for uptake, "physical endocytosis". METHODOLOGY/PRINCIPAL FINDINGS:Herein, we investigate the role of membrane lipid phases on Penetratin induced membrane deformations (liquid ordered such as in "raft" microdomains versus disordered fluid "non-raft" domains) in membrane models. Experimental data show that zwitterionic lipid headgroups take part in the interaction with Penetratin suggesting that the external leaflet lipids of cells plasma membrane are competent for peptide interaction in the absence of net negative charges. NMR and X-ray diffraction data show that the membrane perturbations (tubulation and vesiculation) are associated with an increase in membrane negative curvature. These effects on curvature were observed in the liquid disordered but not in the liquid ordered (raft-like) membrane domains. CONCLUSIONS/SIGNIFICANCE:The better understanding of the internalisation mechanisms of protein transduction domains will help both the understanding of the mechanisms of cell communication and the development of potential therapeutic molecular vectors. Here we showed that the membrane targets for these molecules are preferentially the fluid membrane domains and that the mechanism involves the induction of membrane negative curvature. Consequences on cellular uptake are discussed

Non-Metabolic Membrane Tubulation and Permeability Induced by Bioactive Peptides

BACKGROUND: Basic cell-penetrating peptides are potential vectors for therapeutic molecules and display antimicrobial activity. The peptide-membrane contact is the first step of the sequential processes leading to peptide internalization and cell activity. However, the molecular mechanisms involved in peptide-membrane interaction are not well understood and are frequently controversial. Herein, we compared the membrane activities of six basic peptides with different size, charge density and amphipaticity: Two cell-penetrating peptides (penetratin and R9), three amphipathic peptides and the neuromodulator substance P. METHODOLOGY/PRINCIPAL FINDINGS: Experiments of X ray diffraction, video-microscopy of giant vesicles, fluorescence spectroscopy, turbidimetry and calcein leakage from large vesicles are reported. Permeability and toxicity experiments were performed on cultured cells. The peptides showed differences in bilayer thickness perturbations, vesicles aggregation and local bending properties which form lipidic tubular structures. These structures invade the vesicle lumen in the absence of exogenous energy. CONCLUSIONS/SIGNIFICANCE: We showed that the degree of membrane permeabilization with amphipathic peptides is dependent on both peptide size and hydrophobic nature of the residues. We propose a model for peptide-induced membrane perturbations that explains the differences in peptide membrane activities and suggests the existence of a facilitated “physical endocytosis,” which represents a new pathway for peptide cellular internalization

La montagne explorée, étudiée et représentée : évolution des pratiques culturelles depuis le xviiie siècle

Le Siècle des lumières, qui consacre l’ouverture des élites européennes à la modernité scientifique, est aussi celui qui pousse les mêmes sociétés vers les sommets et les glaciers des montagnes. Objet de fascination et non plus de crainte, la montagne apparaît, à la suite de Rousseau et Senancour, dans toute sa majesté, à la fois vierge, mystérieuse, repliée sur elle-même et porteuse d’un message d’universalité. Après avoir longtemps suscité peur et préjugés depuis l’Antiquité, la montagne est devenue au xviiie siècle un territoire de conquête et de découverte générant toute une mythologie et un imaginaire qui vont modifier le rapport des sociétés européennes avec le milieu des sommets. Le Congrès national des sociétés historiques et scientifiques rassemble chaque année universitaires, membres de sociétés savantes et jeunes chercheurs. Ce recueil est issu de travaux présentés lors du 142e Congrès sur le thème « Circulations montagnardes, circulations européennes »