1,720,970 research outputs found
Reverse engineering of natural systems by graph theory
Full text linkWith the advent of high-throughput technology, Biological research widened its horizons in terms of biomarkers and mechanisms of action of several diseases and phenotypes. On the other hand, complex diseases, like diabetes, several neurodegenerative pathologies and cancer, are still orphan of a cause and then of a cure. One of the possible reasons is that these are not strictly monogenic diseases since they result from a global interplay between molecular players and master regulators. In this context, where “the whole is something over and above its parts and not just the sum of them all” (Aristotle 384-322 B.C.), is clear that the Cartesian reductionism cannot completely help understand how a disease arises and develops.
Systems Biology comes on the stage here and puts emphasis on whole behavior as being basically indivisible. It sustains the Smuts’s holistic theory according to which whole systems such as cells, tissues, organisms, and populations were proposed to have unique emergent properties and that it was impossible to reassemble the behavior of the whole from the properties of the individual components. Hence, new technologies were necessary to define and understand the behavior of systems. New mathematical models and computational approaches emerged in the past decades. Thereby taking inspiration from the theory of graphs. Aspects of nature that could be explained by the interaction of individual agents were modeled as networks and their properties studied topologically. Speculations on the global structure of biological systems were based on two important assertions: systems have a hierarchical structure, and the structure is held together by numerous linkages to construct very complex networks.
In this work, we retrace this path by first reconstructing and studying a complex molecular system made by gene and microRNA expression profiles in patients affected by colorectal cancer. We show how the study of topological properties of the system helped identifying a tiny subnetwork of master-regulator and effectors that, individually, were associated to poor survival rates when extremely expressed. Group-effects were not captured, until the development of Pyntacle, a cross-platform and open source Python suite of high-performance computing algorithms for the discovery of key-players in networks. Pyntacle is introduced and presented in this work and then used proficiently in two other case studies. The former regards ecological food webs and reports on the
assessment of their nestedness property, which is an indicator of their global robustness and redundancy. The latter is an exploration of the relationships between sex and ageing process in Drosophila melanogaster, which developed into two computational steps: definition of co-expressing modules of genes and identification of sex independent key-players molecules in male and female flies
Day-to-day variability in microarray experiment: a new algorithm to summarize probe levels and minimize this effect
No full textA new algorithm to summarize microarray probe levels taking into account the day-to-day variability
No full textSummarizing probe intensities of Affymetrix GeneChip 3' expression arrays taking into account day-to-day variability
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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
Non-parametric MANOVA methods for detecting differentially expressed genes in RT-PCR experiments
No full textRT-PCR is a quantitative technique of molecular biology used to amplify DNA sequences starting from a sample of mRNA. RT-PCR is typically used to explore gene expression variation across groups of treatment.
Because of the non-normal distribution of data, various authors have proposed nonparametric methods based on the MANOVA approach to deal with this problem. These methods, based on the use of distances (Anderson et al.) and of the use of the medians instead of means (Xu et al.) allow to explore patterns of differential gene expression via global F-ratio test obtained through permutations and subsequent analysis of contrasts.
A non-parametric test for multiple univariate comparisons is then used to evaluate which genes are likely to be differentially expressed across groups.
Results of a study involving 30 mice assigned to one control group and to 4 different treatments are presented. An effect of treatment on gene expression is detected by both methods, with good agreement also with respect to the pre-selected multiple comparisons.
These results are potentially useful to draw out new biological hypothesis to be verified in following designed studies.
Future research will be focused on comparison of such methods with classical strategies for analysing RT-PCR data, to better evaluate their advantages and drawbacks; moreover, work will also concentrate on extending such methods to doubly multivariate design, a context often arising in biological data
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
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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