1,720,979 research outputs found
Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data
No full textIn a previous study it was shown that a simple random Boolean network model, with two input connections per node, can describewith a good approximation (with the exception of the smallest avalanches) the distribution of perturbations in gene expression levelsinduced by the knock-out of single genes in Saccharomyces cerevisiae. Here we address the reason why such a simple model actuallyworks: we present a theoretical study of the distribution of avalanches and show that, in the case of a Poissonian distribution of outgoinglinks, their distribution is determined by the value of the Derrida exponent. This explains why the simulations based on the simple modelhave been effective, in spite of the unrealistic hypothesis about the number of input connections per node. Moreover, we consider herethe problem of the choice of an optimal threshold for binarizing continuous data, and we show that tuning its value provides an evenbetter agreement between model and data, valuable also in the important case of the smallest avalanches. Finally, we also discuss thechoice of an optimal value of the Derrida parameter in order to match the experimental distributions: our results indicate a value slightlybelow the critical value 1
Perturbation in genetic regulatory networks: simulation and experiments
No full textRandom boolean networks (RBN) have been proposed more thanthirty years ago as models of genetic regulatory networks. Recent studies on theperturbation in gene expression levels induced by the knock-out (i.e. silencing)of single genes have shown that simple RBN models give rise to a distributionof the size of the perturbations which is very similar in different model networkrealizations, and is also very similar to the one actually found in experimentaldata concerning a unicellular organism (S.cerevisiae). In this paper we presentfurther results, based upon the same set of experiments, concerning thecorrelation between different perturbations. We compare actual data from S.cerevisiae with the results of simulations concerning RBN models with morethan 6000 nodes, and comment on the usefulness and limitations of RBNmodels
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Extended notion of attractors in noisy random Boolean networks
No full textSince real networks are noisy systems, in this work we investigate thedynamics of the random Boolean networks affected by different size of smallrandom fluctuations. In this case jumps among different attractors are possible,thereby leading to an asymptotic dynamics different from that of the underlyingdeterministic model. The significance of the jumps among attractors is investigated.The notion of “ergodic set” is discussed and generalized in terms of“threshold ergodic set”, a concept that take into account the system lifetime. Inorder to evaluate possible differences due to the topology of the nets the experimentsare effectuated on Erdos-Renyi and scale-free topologies, showing similarbehaviour
THE SIMULATION OF GENE KNOCK-OUT IN SCALE-FREE RANDOM BOOLEAN MODELS OF GENETIC NETWORKS
No full textThis paper describes the effects of perturbations, which simulatethe knock-out of single genes, one at a time, in random Boolean models ofgenetic networks (RBN). The analysis concentrates on the probability distributionof so-called avalanches (defined in the text) in gene expression. Thetopology of the random Boolean networks considered here is of the scale-freetype, with a power-law distribution of outgoing connectivities. The results forthese scale-free random Boolean networks (SFRBN) are compared with thoseof classical RBNs, which had been previously analyzed, and with experimentaldata on S. cerevisiae. It is shown that, while both models approximatethe main features of the distribution of experimental data, SFRBNs tend tooverestimate the number of large avalanches
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Cell-cell interaction and diversity of emergent behaviours
No full textDespite myriads of possible gene expression profiles, cells tend to be found a in a confined number of expression patterns. The dynamics of Boolean models of gene regulatory networks has proven to be a likely candidate for the description of such self-organization phenomena. Since cells do not leave in iso- lation, but they constantly shape their functions in order to adapt to signals from other cells, this raises the question of whether the cooperation among cells en- tails en expansion or a reduction of their possible steady states. Multi Random Boolean Networks (MRBNs) are here introduced as a model for the interaction among cells suitable for the investigation of some generic properties regarding the influence of communication on the diversity of cell behaviours. In spite of its simplicity, the model exhibits a not obvious phenomenon according to which a moderate exchange of products among adjacent cells would foster the spectra of their possible behaviours, which on the other hand would be more similar to one another. On the contrary, a more invasive coupling would lead cells towards homogeneity
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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