1,720,993 research outputs found
DNA loci cross-talk through thermodynamics
Full text linkThe recognition and pairing of specific DNA loci, though crucial for a plenty of important cellular processes, are produced by still mysterious physical mechanisms. We propose the first quantitative model from Statistical Mechanics, able to clarify the interaction allowing such “DNA cross-talk” events. Soluble molecules, which bind some DNA recognition sequences, produce an effective attraction between distant DNA loci; if their affinity, their concentration, and the relative DNA binding sites number exceed given thresholds, DNA colocalization occurs as a result of a thermodynamic phase transition. In this paper, after a concise report on some of the most recent experimental results, we introduce our model and carry out a detailed “in silico” analysis of it, by means of Monte Carlo simulations. Our studies, while rationalize several experimental observations, result in very interesting and testable predictions
Mechanics and dynamics of X-chromosome pairing at X inactivation
Full text linkAt the onset of X-chromosome inactivation, the vital process whereby female mammalian cells equalize X products with
respect to males, the X chromosomes are colocalized along their Xic (X-inactivation center) regions. The mechanism
inducing recognition and pairing of the X’s remains, though, elusive. Starting from recent discoveries on the molecular
factors and on the DNA sequences (the so-called "pairing sites") involved, we dissect the mechanical basis of Xic
colocalization by using a statistical physics model. We show that soluble DNA-specific binding molecules, such as those
experimentally identified, can be indeed sufficient to induce the spontaneous colocalization of the homologous
chromosomes but only when their concentration, or chemical affinity, rises above a threshold value as a consequence of a
thermodynamic phase transition. We derive the likelihood of pairing and its probability distribution. Chromosome dynamics
has two stages: an initial independent Brownian diffusion followed, after a characteristic time scale, by recognition and
pairing. Finally, we investigate the effects of DNA deletion/insertions in the region of pairing sites and compare model
predictions to available experimental data
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No full textMean-Field Theory of the Symmetry Breaking Modelfor X Chromosome Inactivation
No full textX Chromosome Inactivation (XCI) is the process in mammal female cells whereby one of the X chromosomes is silenced to compensate dosage with respect to males. It is still myste- rious how precisely one X chromosome is randomly chosen for inactivation. We discuss here a mean-field theory of the Symmetry Breaking (SB) model of XCI, a Statistical Mechanics model introduced to explain that process. The SB model poses that a single regulatory factor, an aggregate of molecules, is produced which acts to preserve from inactivation one of the X’s. The model illustrates a physical mechanism, originating from a thermodynamic phase transition, for the self-assembling of such a single super-molecular aggregate which can spontaneously break the binding symmetry of equivalent targets. This results in a sharp, yet stochastic, regulatory mechanism of XCI. In particular, we focus here on how the model can predict the effects of genetic deletions
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
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