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Academic literature on the topic 'Réseaux de co-expression'
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Journal articles on the topic "Réseaux de co-expression"
Belzeaux, R. "Comment les gènes s’expriment au cours de la réponse aux antidépresseurs ?" European Psychiatry 29, S3 (November 2014): 555. http://dx.doi.org/10.1016/j.eurpsy.2014.09.359.
Full textNataf, Serge, and Laurent Pays. "Microdissection virtuelle par analyse des réseaux de co-expression génique : application à l’identification des profils moléculaires macrophagiques et lymphocytaires T dans le glioblastome." Morphologie 99, no. 327 (December 2015): 161. http://dx.doi.org/10.1016/j.morpho.2015.09.027.
Full textDissertations / Theses on the topic "Réseaux de co-expression"
Janbain, Ali. "Utilisation d'algorithmes génétiques pour l'identification systématique de réseaux de gènes co-régulés." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTT019/document.
Full textThe aim of this work is to develop a new automatic approach to identify networks of genes involved in the same biological function. This allows a better understanding of the biological phenomena and in particular of the processes involved in diseases such as cancers. Various strategies have been developed to try to cluster genes of an organism according to their functional relationships : classical genetics and molecular genetics. Here we use a well-known property of functionally related genes mainly that these genes are generally co-regulated and therefore co-expressed. This co-regulation can be detected by microarray meta-analyzes databases such as Gemma or COXPRESdb. In a previous work [Al Adhami et al., 2015], the topology of a gene coexpression network was characterized using two description parameters of networks that discriminate randomly selected groups of genes (random modules, RM) from groups of genes with known functional relationship (functional modules, FM), e.g. genes that belong to the same GO Biological Process. We first tested different topological descriptors of the co-expression network to select those that best identify functional modules. Then, we built a database of functional and random modules for which, based on the selected descriptors, we constructed a discrimination model (LDA)[Friedman et al., 2001] allowing, for a given subset of genes, predict its type (functional or not). Based on the similarity method of genes worked by Wang and co-workers [Wang et al., 2007], we calculated a functional similarity score between the genes of a module. We combined this score with that of the LDA model in a fitness function implemented in a genetic algorithm (GA). Starting from a given Gene Ontology Biological Process (GO-BP), AG aimed to eliminate genes that were weakly coexpressed with the largest clique of the GO-BP and to add genes that "improved" the topology and functionality of the module. We tested TopoFunc on the 193 murine GO-BPs comprising 50-100 genes and showed that TopoFunc aggregated a number of novel genes to the initial GO-BP while improving module topology and functional similarity. These studies can be conducted on several species (humans, mice, rats, and possibly chicken and zebrafish) to identify functional modules preserved during evolution
Brunet, Anne-Claire. "Développement d'outils statistiques pour l'analyse de données transcriptomiques par les réseaux de co-expression de gènes." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30373/document.
Full textToday's, new biotechnologies offer the opportunity to collect a large variety and volume of biological data (genomic, proteomic, metagenomic...), thus opening up new avenues for research into biological processes. In this thesis, what we are specifically interested is the transcriptomic data indicative of the activity or expression level of several thousands of genes in a given cell. The aim of this thesis was to propose proper statistical tools to analyse these high dimensional data (n<
Pogorelcnik, Romain. "Decomposition by complete minimum separators and applications." Thesis, Clermont-Ferrand 2, 2012. http://www.theses.fr/2012CLF22301/document.
Full textWe worked on clique minimal separator decomposition. In order to compute this decomposition on a graph G we need to compute the minimal separators of its triangulation H. In this context, the first efforts were on finding a clique minimal separators in a chordal graph. We defined a structure called atom tree inspired from the clique tree to compute and represent the final products of the decomposition, called atoms. The purpose of this thesis was to apply this technique on biological data. While we were manipulating this data using Galois lattices, we noticed that the clique minimal separator decomposition allows a divide and conquer approach on Galois lattices. One biological application of this thesis was the detection of fused genes which are important evolutionary events. Using algorithms we produced in the course of along our work we implemented a program called MosaicFinder that allows an efficient detection of this fusion event and their pooling. Another biological application was the extraction of genes of interest using expression level data. The atom tree structure allowed us to have a good visualization of the data and to be able to compute large datasets
Pogorelcnik, Romain. "Décomposition par séparateurs minimaux complets et applications." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2012. http://tel.archives-ouvertes.fr/tel-00824116.
Full textToueni, Maoulida. "Étude de l'interaction entre Verticillium alfalfae et Medicago truncatula." Thesis, Toulouse, INPT, 2014. http://www.theses.fr/2014INPT0097/document.
Full textVerticllium wilt of alfalfa (Medicago sativa L.) is a vascular disease caused by the soil fungus Verticillium alfalfae. It is one of the most devastating diseases and most difficult to control. Symptoms are leaf yellowing followed by wilting and defoliation. Survival structures which are produced at the end of the disease cycle are a source of inoculum for many years. Fungicide treatment is not efficient, and the only way to control this disease is to breed resistant cultivars. Genetic studies are difficult in M. sativa because it is tetraploid and outcrossing. A pathosystem has been set up in our laboratory in order to study the mechanisms involved in the interaction between V. alfalfae and its host. It involves the model legume plant M. truncatula and strain V31-2 of V. alfalfae. The lines A17 and F83005.5 were identified as respectively resistant and susceptible to V31-2. The first part of this thesis is a comparative study of the infection process of V. alfalfae V31-2 in a compatible and incompatible interaction. The time course of root colonization in lines A17 and F83005.5 was studied with a GFP-expressing strain which confers green fluorescence to the fungus. Observations by confocal microscopy showed that the fungus developed in a similar way in roots of both lines during the first stage of the interaction. Some days later the fungus was not detectable anymore in roots of the resistant line, but has colonized the xylem vessels and grew towards the aerial part of the plant in the susceptible line. Quantification of fungal DNA in roots and aerial parts confirmed these results. This showed that the resistant line A17 was able to suppress the pathogen’s development in the root. It can be concluded that line A17 presents total resistance towards V. alfalfae. The second part of the thesis concerns the role of phytohormones for defence mechanisms against V. alfalfae in M. truncatula. Susceptible and resistant plants were treated with salicylic acid (SA), methyl jasmonate (MeJA), ethylene (ET), auxine and abscissic acid (ABA). Resistance of line A17 was not affected by these treatments, but all hormones except MeJA protected the susceptible line against disease symptoms. However, when fungal DNA was quantified in planta in these assays, only ABA inhibited the pathogen’s development significantly. The third part of this thesis aims at identifying molecular factors involved in resistance and susceptibility. To address this topic, the transcriptome of lines A17 and F83005.5 was compared during the early stages of infection, in inoculated or mock-inoculated plants. A bioinformatics analysis of differentially expressed genes showed that both lines responded to inoculation by inducing genes involved in secondary metabolism and hormone signaling pathways. However, only resistant line A17 showed induction of the expression of putative resistance and signaling genes, genes involved in ABA synthesis and transcription factors. This result confirms our hypothesis that ABA might be an important factor in M. truncatula resistance against V. alfalfae. Gene network analysis of co-expressed genes showed a disorganised response in the susceptible line, whereas in the resistant line the response was highly organised and turned to defence. Taken together, this work describes for the first time defence mechanisms against V. alfalfae in M. truncatula. The results show that resistance of line A17 is different from resistance mechanisms Verticillium resistance described in tomato and cotton. Several approaches for future research are presented in order to test our hypotheses concerning genes and molecules putatively involved in this interaction. With regard to applied research, defence and signaling genes identified in this work may be useful for the improvement of alfalfa, after functional validation
Marti, Marimon Maria Eugenia. "3D genome conformation and gene expression in fetal pig muscle at late gestation." Thesis, Toulouse, INPT, 2018. http://www.theses.fr/2018INPT0099.
Full textIn swine breeding industry, sows have been selected for decades on their prolificacy in order to maximize meat production. However, this selection is associated with a higher mortality of newborns. In this context, the skeletal fetal muscle is essential for the piglet’s survival, as it is necessary for motor functions and thermoregulation. Besides, the three-dimensional structure of the genome has been proven to play an important role in gene expression regulation. Thus, in this project, we have focused our interest on the 3D genome conformation and gene expression in porcine muscle nuclei at late gestation. We have initially developed an original approach in which we combined transcriptome data with information of nuclear locations (assessed by 3D DNA FISH) of a subset of genes, in order to build gene co expression networks. This study has revealed interesting nuclear associations involving IGF2, DLK1 and MYH3 genes, and highlighted a network of muscle specific interrelated genes involved in the development and maturity of fetal muscle. Then, we assessed the global 3D genome conformation in muscle nuclei at 90 days and 110 days of gestation by using the High-throughput Chromosome Conformation Capture (Hi¬ C) method. This study has allowed identifying thousands of genomic regions showing significant differences in 3D conformation between the two gestational ages. Interestingly, some of these genomic regions involve the telomeric regions of several chromosomes that seem to be preferentially clustered at 90 days. More important, the observed changes in genome structure are significantly associated with variations in gene expression between the 90th and the 110th days of gestation
Scott-Boyer, Marie Pier. "Études de réseaux d’expression génique : utilité pour l’élucidation des déterminants génétiques des traits complexes." Thèse, 2013. http://hdl.handle.net/1866/10133.
Full textComplex quantitative traits are measurable characteristics of living organisms resulting from the interaction between multiple genes and environmental factors. Genetic loci associated with complex trait are called "quantitative trait loci" (QTL). Recently, considering the expression levels of thousands of genes as quantitative traits, it has become possible to detect "expression QTLs " (eQTL). These eQTL are considered intermediate phenotypes and are used to better understand the biological architecture of complex traits. However the majority of studies still try to identify a causal mutation in a single gene. This approach can only meet success in situations where the gene incriminate as a major effect on the complex trait, and therefore can not elucidate the situations where complex traits result from interactions between various genes. This thesis proposes a more comprehensive approach to: 1) take into account the possible interactions between multiple genes for the detection of eQTLs and 2) consider how polymorphisms affecting the expression of several genes in a module of co-expression may contribute to quantitative complex traits. Our contributions are as follows: We have developed a tool using multivariate analysis techniques to detect eQTLs, and have shown that this tool increases the sensitivity of detection of a particular class of eQTLs. Based on the data analysis of gene expression in recombinant inbred strains mice tissues, we have shown that some polymorphisms may affect the expression of several genes in domain of co-expression. Combining eQTLs detection studies with network of co-expression genes analysis in recombinant inbred strains mice, we showed that a genetic locus could be linked to both the expression of multiple genes at a domain of gene co-expression and a specific complex trait (i.e. left ventricular mass). Our studies have detected several mechanisms by which genetic polymorphisms may be associated with the expression of several genes, and may themselves be linked to quantitative complex traits.