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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3

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    Stratified partial likelihood estimation
    (Elsevier, 1999) Ridder, Gert; Department of Economics; Tunalı, Fehmi İnsan; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 105635
    When multiple durations are generated by a single unit, they may be related in a way that is not fully captured by the regressors. The omitted unit-specific variables might vary over the durations, They might also be correlated with the variables in the regression component. We propose an estimator that responds to these concerns and develop a specification test for detecting unobserved unit-specific effects, Data from Malaysia reveal that concentration of child mortality in some families is imperfectly explained by observed explanatory variables, and that failure to control for unobserved heterogeneity seriously biases the parameter estimates.
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    Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins
    (Public Library Science, 2022) Wojciechowski, Jakub W.; Gasior-Glogowska, Marlena; Coustou, Virginie; Szulc, Natalia; Szefczyk, Monika; Kopaczynska, Marta; Saupe, Sven J.; Dyrka, Witold; Tekoğlu, Tahsin Emirhan; PhD Student; Graduate School of Sciences and Engineering; N/A
    NLR proteins are intracellular receptors constituting a conserved component of the innate immune system of cellular organisms. In fungi, NLRs are characterized by high diversity of architectures and presence of amyloid signaling. Here, we explore the diverse world of effector and signaling domains of fungal NLRs using state-of-the-art bioinformatic methods including MMseqs2 for fast clustering, probabilistic context-free grammars for sequence analysis, and AlphaFold2 deep neural networks for structure prediction. In addition to substantially improving the overall annotation, especially in basidiomycetes, the study identifies novel domains and reveals the structural similarity of MLKL-related HeLo- and Goodbye-like domains forming the most abundant superfamily of fungal NLR effectors. Moreover, compared to previous studies, we found several times more amyloid motif instances, including novel families, and validated aggregating and prion-forming properties of the most abundant of them in vitro and in vivo. Also, through an extensive in silico search, the NLR-associated amyloid signaling was identified in basidiomycetes. The emerging picture highlights similarities and differences in the NLR architectures and amyloid signaling in ascomycetes, basidiomycetes and other branches of life.
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    Bias, Type I error rates, and statistical power of a latent mediation model in the presence of violations of invariance
    (Sage, 2018) Olivera-Aguilar, Margarita; Rikoon, Samuel H.; Gonzalez Oskar; MacKinnon David P.; Department of Psychology; Sakarya, Yasemin Kisbu; Faculty Member; Department of Psychology; College of Social Sciences and Humanities; 219275
    When testing a statistical mediation model, it is assumed that factorial measurement invariance holds for the mediating construct across levels of the independent variable X. The consequences of failing to address the violations of measurement invariance in mediation models are largely unknown. The purpose of the present study was to systematically examine the impact of mediator noninvariance on the Type I error rates, statistical power, and relative bias in parameter estimates of the mediated effect in the single mediator model. The results of a large simulation study indicated that, in general, the mediated effect was robust to violations of invariance in loadings. In contrast, most conditions with violations of intercept invariance exhibited severely positively biased mediated effects, Type I error rates above acceptable levels, and statistical power larger than in the invariant conditions. The implications of these results are discussed and recommendations are offered.
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    Anomalies in the transcriptional regulatory network of the Yeast Saccharomyces cerevisiae
    (Elsevier, 2010) N/A; Department of Physics; Tuğrul, Murat; Kabakçıoğlu, Alkan; N/A; Faculty Member; Department of Physics; Graduate School of Sciences and Engineering; College of Sciences; N/A; 49854
    We investigate the structural and dynamical properties of the transcriptional regulatory network of the Yeast Saccharomyces cerevisiae and compare it with two "unbiased" ensembles: one obtained by reshuffling the edges and the other generated by mimicking the transcriptional regulation mechanism within the cell. Both ensembles reproduce the degree distributions (the first-by construction-exactly and the second approximately), degree-degree correlations and the k-core structure observed in Yeast. An exceptionally large dynamically relevant core network found in Yeast in comparison with the second ensemble points to a strong bias towards a collective organization which is achieved by subtle modifications in the network's degree distributions. We use a Boolean model of regulatory dynamics with various classes of update functions to represent in vivo regulatory interactions. We find that the Yeast's core network has a qualitatively different behavior, accommodating on average multiple attractors unlike typical members of both reference ensembles which converge to a single dominant attractor. Finally, we investigate the robustness of the networks and find that the stability depends strongly on the used function class. The robustness measure is squeezed into a narrower band around the order-chaos boundary when Boolean inputs are required to be nonredundant on each node. However, the difference between the reference models and the Yeast's core is marginal, suggesting that the dynamically stable network elements are located mostly on the peripherals of the regulatory network. Consistently, the statistically significant three-node motifs in the dynamical core of Yeast turn out to be different from and less stable than those found in the full transcriptional regulatory network.