Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
Motivation: Gene fusion is an important evolutionary process. It can yield valuable information to infer the interactions and functions of proteins. Fused genes have been identified as non-transitive patterns of similarity in triplets of genes. To be computationally tractable, this approach usually imposes an a priori distinction between a dataset in which fused genes are searched for, and a dataset that may have provided genetic material for fusion. This reduces the `genetic space' in which fusion can be discovered, as only a subset of triplets of genes is investigated. Moreover, this approach may have a high-false-positive rate, and it does not identify gene families descending from a common fusion event. Results: We represent similarities between sequences as a network. This leads to an efficient formulation of previous methods of fused gene identification, which we implemented in the Python program FusedTriplets. Furthermore, we propose a new characterization of families of fused genes, as clique minimal separators of the sequence similarity network. This well-studied graph topology provides a robust and fast method of detection, well suited for automatic analyses of big datasets. We implemented this method in the C++ program MosaicFinder, which additionally uses local alignments to discard false-positive candidates and indicates potential fusion points. The grouping into families will help distinguish sequencing or prediction errors from real biological fusions, and it will yield additional insight into the function and history of fused genes.
ISSN: 1367-4803

hal-01544795
https://hal.archives-ouvertes.fr/hal-01544795
DOI : 10.1093/bioinformatics/btt049

Résumé : Ce travail vise à mettre en place un système de fusion de sources d'information basé sur la Théorie des Fonctions de Croyance (TFC) et adapté aux contextes des images forestières. La TFC engendre des temps de calcul importants lorsque la cardinalité du cadre de discernement devient grande. Ainsi, nous avons proposé en premier lieu une méthode de réduction du référentiel de définition permettant d'éviter l'explosion combinatoire en restreignant le calcul sur les hypothèses estimées pertinentes et déterminées à partir des histogrammes des classes issues de la phase d'apprentissage. Ensuite, nous avons proposé des techniques d'estimation de fonctions de masse spectrales, texturales, contextuelles et structurelles. L'information multi-fractale a été utilisée comme signature de texture, ainsi l'image de Hôlder a constitué une source d'information pour l'estimation de la masse texturale. Un autre apport consiste à proposer une approche de transfert de masse basée sur l'information contextuelle, en exploitant l'image des couronnes d'arbres comme une source déduite. L'implémentation d'algorithmes de détection de couronnes d'arbres nous a permis d'extraire des mesures sur les couronnes que nous avons utilisées en tant qu'attributs pour l'estimation des fonctions de masse. Nos expérimentations montrent des taux de classification assez satisfaisants et une adéquation de notre approche de fusion à une classification à l'arbre près
This thesis aims to develop an information source fusion system based on belief functions theory (BFT) and adapted t forest images context (especially high resolution images). Applications of BFT to image classification result in th assignment of each image point to a c1ass or a subset of classes based on the mass functions estimation expressing th belief of an event. BFT leads to significant computation time when the cardinality of the set of definition become large. Thus, we first proposed a method to reduce the frame of discernment in order te avoid the combinatorial explosio by restricting the calculation on the hypotheses of the set of definition deduced from the classes histograms determine from the learning phase. Then, we proposed spectral, texturai, contextual and structural mass functions technique estimation. Multi-fractal information was used as texture signature and Hôlder image has been a source ( information for estimating the texturai mass. Another contribution is the integration of trees crowns image as derive source and the proposai of an approach to mass transfer based on contextual information inside and outside a crown. Th implementation of detection trees crowns algorithms allowed us to extract measurements on trees. These measurement are used as attributes for mass functions estimation. Our experiments and comparisons with other methods show quit satisfactory classification rate with spectral and textural approaches and adequacy of our fusion approach to contextu and structural information for trees classification

http://www.theses.fr/2011AGUY0434/document

Éditeur(s) : HAL CCSD
Résumé : En traitement d'image, avant toute exploitation de résultats d'une segmentation d'image, il est souvent nécessaire de réaliser une opération de fusion. Le but est de créer une partition formée de composantes connexes, modélisant les objets présents dans l'image. La segmentation initiale des images est souvent obtenue par l'exploitation d'attributs de bas-niveau (couleur, texture, forme...). La théorie Gestalt permet de prendre en compte des informations d'un niveau supérieur qui s'appuient sur l'organisation spatiale des objets et groupement d'objets initialement segment'es. Dans cet article, nous proposons une méthode de fusion de régions. L'originalité des travaux repose sur l'ajout d'un nouveau critère qui, associé aux critères Gestalt, permet de prendre en compte les objets jugés d'intérêt par le photographe, c'est-'a-dire les objets aux contours nets. Les régions associées aux objets d'intérêts seront alors préservées alors que les régions floues ou aux contours flous, situées dans l'arrière-plan, auront tendance 'a fusionner entre elles.
Journée du GdR Mathématique de l'Optimisation et Application (MOA)
Saint-François, Guadeloupe

hal-00706538
https://hal.archives-ouvertes.fr/hal-00706538

Éditeur(s) : HAL CCSD IEEE Computer Society
Résumé : 5 pages, 2 figures, composed with Microsoft Word. Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003). Edinburgh, Écosse, 3-6 août 2003. Également disponible à l'URL : http://www.cse.salford.ac.uk/prima/ICDAR2003/Papers/0100_563_likforman_l.pdf
International audience
In the frame of a Unified Messaging System, a crucial task of the system is to provide the user with key information on every message received, like keywords reflecting the object of the message, or the name of the sender. However, in the case of facsimiles, this information is not as easy to detect as in the case of e-mails, since no standard headers are defined. The aim of the present work is to identify and extract a specific information (the name of the sender) from a fax cover page. For this purpose, methods based on image document analysis (OCR recognition, physical blocks selection), and text analysis methods (optimised dictionary lookup, local grammar rules), are implemented to work in parallel. The fusion of their results brings a more accurate guess than any of the methods would achieve separately.
Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003)
Edinburgh, United Kingdom

hal-00328998
https://hal.archives-ouvertes.fr/hal-00328998
DOI : 10.1109/ICDAR.2003.1227724

Éditeur(s) : HAL CCSD
Résumé : International audience
The fusion of regions from segmentation is often a required step in order to analyze objects in the scene. It allows to group under a same closure property the partitions of an image, which denote the same object. In this way, several studies have been made. Most of the algorithms are based on global information to evaluate the relevance of region combinations and fusion. In this paper, we propose a merging process based on Gestalt vision's theory. The particularity of our method is to preserve photographer's region of interest thanks to the definition of a new criterion based on Di Zenzo gradient. Thus, region fusion preserves photographer's relevant objects of the scene. The performance of the proposed method is evaluated using various natural images, including Berkeley image database and its accuracy is shown.
Color and Imaging Conference
San Jose, CA, United States

hal-00637144
https://hal.archives-ouvertes.fr/hal-00637144

Éditeur(s) : HAL CCSD
Résumé : International audience
The extraction of knowledge from social networks is an area that has experienced significant growth in recent years. Indeed, thanks to the improvement of storage and calculation capacities, and the heterogeneity of data that can currently be extracted, much effort has been made to go beyond traditional knowledge, by proposing new kinds of patterns that take into account the context. However, while many works were interested in designing new patterns of knowledge or in optimizing existing approaches, few studies have been focused in merging patterns and on the useful knowledge emerging from such fusions. In this work, we focus on two network clustering approaches, able to extract two distinct kinds of patterns, and we seek to understand both the intersections that can exist between them and the knowledge that emerges from their fusion. The first is the classical nodes clustering approach that consists in searching for communities into a network. The second is the search for frequent conceptual links, a new link clustering approach that aims identifying frequent links between groups of nodes sharing common attributes. We propose a set of original measures that aim to evaluate the amount of shared information between these patterns when they are extracted from a same network. These measures are applied to three datasets and demonstrate the interest in simultaneously considering several sources of knowledge.
Advances in Knowledge Discovery and Management (AKDM)

hal-01514227
https://hal.archives-ouvertes.fr/hal-01514227
DOI : 10.1007/978-3-319-45763-5_13

Éditeur(s) : HAL CCSD National Academy of Sciences
Résumé : International audience
The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the ``recycling'' of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance.
ISSN: 0027-8424

hal-01544793
https://hal.archives-ouvertes.fr/hal-01544793
DOI : 10.1073/pnas.1517551113

Éditeur(s) : HAL CCSD
Résumé : International audience
During the last decade, GIS have suffered of the lack of structured information and semantic definition of the data. The numerous origins of the data and the spatial localization of the object inferred many inconsistencies among them. Indeed, the way to collect data and the level of sampling of the boundary differ from one application to another and from one expert to another. This leads to different representations of the same reality and different models of semantically identical objects or boundaries. To allow the matching of the objects, or parts of the objects, when combining different information layers we introduced a conceptual layer which described a scene with concepts and spatial relationships based on the definition of an ontology. This layer allows detecting and solving conflicts between the common boundaries of two objects. We present in this paper the specification and the way to build and use the ontology.
Geoprocessing proceedings
Gosier, Guadeloupe

hal-00602257
https://hal.archives-ouvertes.fr/hal-00602257