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Search Results: 1 - 10 of 26988 matches for " Jean-Fran?ois Gibrat "
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Amino acid "little Big Bang": Representing amino acid substitution matrices as dot products of Euclidian vectors
Karel Zimmermann, Jean-Franois Gibrat
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-4
Abstract: We present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices.This vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.Methods for analyzing protein sequences rest on the underlying amino acid representation. For many purposes, such as sequence comparisons, amino acids are represented by a one-letter code and their similarity is "summed up" in substitution (scoring) matrices.Elements of these matrices represents the score of substituting an amino acid by another one in homologous proteins. It has been shown [1] that the general form of such an element is:where sab is the matrix element corresponding to amino acids a and b, Pab is the probability to find these amino acids aligned together in known protein families, and Pa, Pb are the corresponding background frequencies. λ is a scaling factor. PAM [2] and BLOSUM [3] matrices are computed accordingly. Such a ratio compare the probability of an event under two alternative hypotheses: i) the amino acids are aligned because the two sequences are evolutionary related or ii) the alignment is due to a chance occurrence. Adding such scores when comparing two sequences therefore amounts to maximizing the probability that the two sequences are evolutionary related.Protein substitution matrices play a centr
Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?
Jean-Franois Taly, Antoine Marin, Jean-Franois Gibrat
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-6
Abstract: For three test sequences whose native structures belong to the all-α, all-β and αβ classes we built a set of models intended to cover the whole spectrum: from a perfect model, i.e., the native structure, to a very poor model, i.e., a random alignment of the test sequence with a structure belonging to another structural class, including several intermediate models based on fold recognition alignments. We submitted these models to 11 ns of MD simulations at three different temperatures. We monitored along the corresponding trajectories the mean of the Root-Mean-Square deviations (RMSd) with respect to the initial conformation, the RMSd fluctuations, the number of conformation clusters, the evolution of secondary structures and the surface area of residues. None of these criteria alone is 100% efficient in discriminating correct from erroneous models. The mean RMSd, RMSd fluctuations, secondary structure and clustering of conformations show some false positives whereas the residue surface area criterion shows false negatives. However if we consider these criteria in combination it is straightforward to discriminate the two types of models.The ability of discriminating correct from erroneous models allows us to improve the specificity and sensitivity of our fold recognition method for a number of ambiguous cases.The last 10 years have witnessed steady progress in the prediction of the three-dimensional (3D) structure of proteins from their amino acid sequence [1]. Most current approaches, ranging from de novo to fold recognition (threading) techniques, are based on simplified "energy" potentials (with a few exceptions such as the UNRES force field [2]). These empirical potentials, often more appropriately referred to as score functions, are derived from statistical analyses of structural features observed in known 3D structures: residue-wise interactions, secondary structure propensities, residue surface, etc. They are used with a reduced representation of the polypepti
Analysis of an optimal hidden Markov model for secondary structure prediction
Juliette Martin, Jean-Franois Gibrat, Franois Rodolphe
BMC Structural Biology , 2006, DOI: 10.1186/1472-6807-6-25
Abstract: Our HMM is designed without prior knowledge. It is chosen within a collection of models of increasing size, using statistical and accuracy criteria. The resulting model has 36 hidden states: 15 that model α-helices, 12 that model coil and 9 that model β-strands. Connections between hidden states and state emission probabilities reflect the organization of protein structures into secondary structure segments. We start by analyzing the model features and see how it offers a new vision of local structures. We then use it for secondary structure prediction. Our model appears to be very efficient on single sequences, with a Q3 score of 68.8%, more than one point above PSIPRED prediction on single sequences. A straightforward extension of the method allows the use of multiple sequence alignments, rising the Q3 score to 75.5%.The hidden Markov model presented here achieves valuable prediction results using only a limited number of parameters. It provides an interpretable framework for protein secondary structure architecture. Furthermore, it can be used as a tool for generating protein sequences with a given secondary structure content.Predicting the secondary structure of a protein is often a first step toward 3D structure prediction of a particular protein. In comparative modeling, secondary structure prediction is used to refine sequence alignments, or to improve the detection of distant homologs [1]. Moreover, it is of prime importance when prediction is made without a template [2]. For all these reasons protein secondary structure prediction has remained an active field for years. Virtually all statistical and learning methods have been applied to this task. Nowadays, the best methods achieve prediction rate of about 80% using homologous sequence information. A survey of the Eva on-line evaluation [3] shows that the top performing methods include several approaches based on neural networks, e.g. PSIPRED by Jones et al [4], PROFsec and PHDpsi by Rost et al [5]. Recentl
Protein secondary structure assignment revisited: a detailed analysis of different assignment methods
Juliette Martin, Guillaume Letellier, Antoine Marin, Jean-Franois Taly, Alexandre G de Brevern, Jean-Franois Gibrat
BMC Structural Biology , 2005, DOI: 10.1186/1472-6807-5-17
Abstract: To address these problems, we have developed a method for secondary structure assignment, called KAKSI. Assignments made by KAKSI are compared with assignments given by DSSP, STRIDE, XTLSSTR, PSEA and SECSTR, as well as secondary structures found in PDB files, on 4 datasets (X-ray structures with different resolution range, NMR structures).A detailed comparison of KAKSI assignments with those of STRIDE and PSEA reveals that KAKSI assigns slightly longer helices and strands than STRIDE in case of one-to-one correspondence between the segments. However, KAKSI tends also to favor the assignment of several short helices when STRIDE and PSEA assign longer, kinked, helices. Helices assigned by KAKSI have geometrical characteristics close to those described in the PDB. They are more linear than helices assigned by other methods. The same tendency to split long segments is observed for strands, although less systematically. We present a number of cases of secondary structure assignments that illustrate this behavior.Our method provides valuable assignments which favor the regularity of secondary structure segments.In 1951, Pauling and Corey predicted the existence of two periodic motifs in protein structures: the α-helix [1] and the β-sheet [2] which turned out to be major features of protein architecture. Secondary structures, because they allow a simple and intuitive description of 3D structures, are widely employed in a number of structural biology applications. For instance, they are used for structure comparison [3] and structure classification [4,5]. They also provide a natural frame for structure visualization [6,7].In recent years, secondary structures have come to play a major role in a number of methods aiming at predicting protein 3D-structures. Indeed, being able to predict accurately secondary structure elements along the sequence provides a good starting point toward elucidating the 3D-structure [8,9]. Current algorithms for predicting the secondary structure
CompaGB: An open framework for genome browsers comparison
Thomas Lacroix, Valentin Loux, Annie Gendrault, Jean-Franois Gibrat, Hélène Chiapello
BMC Research Notes , 2011, DOI: 10.1186/1756-0500-4-133
Abstract: To assist in this task, we propose a community-based framework based on two cornerstones: (i) the implementation of industry promoted software qualification method (QSOS) adapted for genome browser evaluations, and (ii) a web resource providing numerous facilities either for visualizing comparisons or performing new evaluations. We formulated 60 criteria specifically for genome browsers, and incorporated another 65 directly from QSOS's generic section. Those criteria aim to answer versatile needs, ranging from a biologist whose interest primarily lies into user-friendly and informative functionalities, a bioinformatician who wants to integrate the genome browser into a wider framework, or a computer scientist who might choose a software according to more technical features. We developed a dedicated web application to enrich the existing QSOS functionalities (weighting of criteria, user profile) with features of interest to a community-based framework: easy management of evolving data, user comments...The framework is available at http://genome.jouy.inra.fr/CompaGB webcite. It is open to anyone who wishes to participate in the evaluations. It helps the scientific community to (1) choose a genome browser that would better fit their particular project, (2) visualize features comparatively with easily accessible formats, such as tables or radar plots and (3) perform their own evaluation against the defined criteria. To illustrate the CompaGB functionalities, we have evaluated seven genome browsers according to the implemented methodology. A summary of the features of the compared genome browsers is presented and discussed.The diversity of tools available for visualizing and browsing genomic data has increased dramatically over the last years: Bluejay [1], GenoMap [2], GenomeComp [3], GenomeViz [4], DiProGB [5] to cite but a few. Projects aiming at supplanting or complementing current genomes browsers (GBs) are blooming as well. Although these different GBs provide the b
Recent Advances in Solving the Protein Threading Problem
Rumen Andonov,Guillaume Collet,Jean-Franois Gibrat,Antoine Marin,Vincent Poirriez,Nikola Yanev
Computer Science , 2007,
Abstract: The fold recognition methods are promissing tools for capturing the structure of a protein by its amino acid residues sequence but their use is still restricted by the needs of huge computational resources and suitable efficient algorithms as well. In the recent version of FROST (Fold Recognition Oriented Search Tool) package the most efficient algorithm for solving the Protein Threading Problem (PTP) is implemented due to the strong collaboration between the SYMBIOSE group in IRISA and MIG in Jouy-en-Josas. In this paper, we present the diverse components of FROST, emphasizing on the recent advances in formulating and solving new versions of the PTP and on the way of solving on a computer cluster a million of instances in a easonable time.
An Ethnomethodological Perspective on the Conflict between Magistrates and Journalists in Cameroon  [PDF]
Jean-Franois Nguegan, Thomas Essono
Advances in Journalism and Communication (AJC) , 2015, DOI: 10.4236/ajc.2015.34013
Abstract: The report of the magistrate profession to that of a journalist in Cameroon can be studied from the perspective both of the sociology of professions and sociology of the conflict; the actors, who belong to different territories, are usually against the quality, legitimacy and competence required to deal with media information, and judicial control, individual freedom. This relationship is mainly studied in this research in terms of symbolic interactionism, to emphasize first of all on the importance that judges and journalists themselves give to their profession and secondly on the rationality of their game in the construction and the demarcation of their respective territories. This article is a contribution to the study of the discourse of these two groups of professionals who compete with each other.
Adipocytes modulate vascular smooth muscle cells migration potential through their secretions  [PDF]
Souhad El Akoum, Isabelle Cloutier, Jean-Franois Tanguay
Journal of Diabetes Mellitus (JDM) , 2013, DOI: 10.4236/jdm.2013.34035

Impairment of vascular smooth muscle cells (VSMC) is recognized as a predisposition factor for atherosclerosis development. We hypothesize that the metabolic syndrome has a direct impact on VSMC migration and phenotypic switching, which may increase the incidence of atherosclerotic events. Aortic VSMC were extracted from 10 weeks old C57BL6 mice and incubated for 24 hr in adipocytes conditioned cell culture medium. Adipocytes were extracted from diabetic C57BL6 male mice fed with either a vegetal or an animal High-Fat-Diet (HFD) for 20 weeks. Migration of VSMC in response to conditioned media stimulations was significantly modulated compared to control. The most extended effects on VSMC were triggered by adipocytes from mice fed with animal HFD. These effects were concurrent with increased leptin concentrations and decreased adiponectin levels in conditioned media. A significant up-regulation of CD36 mRNA level was found in VSMC treated with adipocytes from HFD-fed mice. In conclusion, we have shown that the development of adipocyte-induced VSMC alterations is linked to diet fatty acid composition and the degree of metabolic alterations. The modulation of adipokine secretions in the adipose tissue that is linked to metabolic alterations may alter the physiology of VSMC and thus accelerate the development of metabolic-related vascular diseases.

Universality in Statistical Measures of Trajectories in Classical Billiard Systems  [PDF]
Jean-Franois Laprise, Ahmad Hosseinizadeh, Helmut Kr?ger
Applied Mathematics (AM) , 2015, DOI: 10.4236/am.2015.68132
Abstract: For classical billiards, we suggest that a matrix of action or length of trajectories in conjunction with statistical measures, level spacing distribution and spectral rigidity, can be used to distinguish chaotic from integrable systems. As examples of 2D chaotic billiards, we considered the Bunimovich stadium billiard and the Sinai billiard. In the level spacing distribution and spectral rigidity, we found GOE behaviour consistent with predictions from random matrix theory. We studied transport properties and computed a diffusion coefficient. For the Sinai billiard, we found normal diffusion, while the stadium billiard showed anomalous diffusion behaviour. As example of a 2D integrable billiard, we considered the rectangular billiard. We found very rigid behaviour with strongly correlated spectra similar to a Dirac comb. These findings present numerical evidence for universality in level spacing fluctuations to hold in classically integrable systems and in classically fully chaotic systems.
Oxytocin and Collective Bargaining: Propositions for a New Research Protocol  [PDF]
Jean-Franois Tremblay, Sébastien Rivard, Eric Gosselin
American Journal of Industrial and Business Management (AJIBM) , 2017, DOI: 10.4236/ajibm.2017.77063
Abstract: This paper contributes to collective bargaining research by providing a causal theoretical biological link path between negotiation behaviors and their substantive and relational results. Specifically, the role of oxytocin is described in light of the scientific knowledge that comes from organizational neurosciences, neuroeconomics and, psychology fields. The properties of the hormone, its place in neuroeconomics research and, their links with the psychology of the collective bargaining processes are discussed to determine guidelines for a new experimental protocol meant to study decision-making processes during collective bargaining. In addition, the conceptual model of strategic negotiations serves as a theoretical framework to consolidate the propositions that can be deduced from the results of the interaction processes in collective bargaining according to two dimensions of the outcome of the negotiations. Finally, the parameters of a new experimental protocol derived from the trust game are presented for the first time. This new game presents a more ecological perspective and is developed to offer a better fit with the specific domain of collective bargaining.
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