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Robust Supervised and Unsupervised Statistical Learning for HIV Type 1 Coreceptor Usage Analysis
No full textHuman immunodeficiency virus type 1 (HIV-1) isolates differ in their use of coreceptors to enter target cells. This has important implications for both viral pathogenicity and susceptibility to entry inhibitors, recently approved or under development. Predicting HIV-1 coreceptor usage on the basis of sequence information is a challenging task, due to the high variability of the envelope. The associations of the whole HIV-1 envelope genetic features (subtype, mutations, insertions-deletions, physicochemical properties) and clinical markers (viral RNA load, CD8(+), CD4(+) T cell counts) with viral tropism were investigated, using a set of 2896 (659 after filter, 593 patients) sequence-tropism pairs available at the Los Alamos HIV database. Bootstrapped hierarchical clustering was used to assess mutational covariation. Univariate and multivariate analysis was performed to assess the relative importance of different features. Different machine learning (logistic regression, support vector machines, decision trees, rule bases, instance based reasoning) and feature selection (filter and embedded) methods, along with loss functions (accuracy, AUC of ROC curves, sensitivity, specificity, f-measure), were applied and compared for the classification of X4 variants. Extra-sample error estimation was assessed via multiple cross-validation and adjustments for multiple testing. A high-performing, compact, and interpretable logistic regression model was derived to infer HIV-1 coreceptor tropism for a given patient [accuracy = 92.76 (SD 3.07); AUC = 0.93 (SD 0.04)]
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Variations on the Author
Get PDF“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
Predictors of First-Line Antiretroviral Therapy Discontinuation due to Drug-related Adverse Events in HIV-infected Patients
No full textAppropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe 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
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