Nucleosome organization plays a key role in the regulation of gene expression. However, despite the striking advances in the accuracy of nucleosome maps, there are still severe discrepancies on individual nucleosome positioning and how this influences gene regulation. The variability among nucleosome maps, which precludes the fine analysis of nucleosome positioning, might emerge from diverse sources. We have carefully inspected the extrinsic factors that may induce diversity by the comparison of microccocal nuclease (MNase)-Seq derived nucleosome maps generated under distinct conditions. Furthermore, we have also explored the variation originated from intrinsic nucleosome dynamics by generating additional maps derived from cell cycle synchronized and asynchronous yeast cultures. Taken together, our study has enabled us to measure the effect of noise in nucleosome occupancy and positioning and provides insights into the underlying determinants. Furthermore, we present a systematic approach that may guide the standardization of MNase-Seq experiments in order to generate reproducible genome-wide nucleosome patterns.
Arrow categories establish a categorical and algebraic description of -fuzzy relations, i.e., relations that use membership values from an arbitrary but fixed complete Heyting algebra . With other words arrow categories describe the fixed-basis case. In this paper we are interested in the variable-basis case, i.e., the case where relations between different objects may use different membership values. We will investigate the structure of the collection of lattices of membership values within a given Dedekind category. This will lead to a complete characterization of the variable-basis case in this context.
Photons emitted by extragalactic sources provide an opportunity to test quantum gravity effects that modify the speed of light in vacuum. Studying the arrival times of these cosmic messengers further constrains the energy scales involved.
In this paper we describe a non-nested level-based representation of fuzziness, closely related to some existing models and concepts in the literature. Our objective is to motivate the use of this non-nested model by describing its theoretical possibilities, and illustrating them with some existing applications. From a theoretical point of view, we discuss the semantics of the representation, which goes beyond and has as a particular case fuzzy sets as represented by a collection of . In addition, the proposed operations on level-based representations, contrary to those of existing fuzzy set theories, satisfy all the properties of Boolean logic. We discuss the contributions of the representation and operation by levels to practical applications, in particular for extending crisp notions to the fuzzy case. In this respect, an important contribution of the proposal is that fuzzy mathematical objects (not only sets and the corresponding predicates) and operations are uniquely and easily defined as extensions of their crisp counterparts. In order to illustrate this claim, we recall level representations of quantities (gradual numbers) and their complementarity to fuzzy intervals (often inappropriately called fuzzy numbers). ► We provide a representation of fuzziness using a finite subset of levels in (0,1]. ► Fuzzy mathematical objects are an assignment of their crisp counterparts to levels. ► Contrary to fuzzy sets, crisp representatives are not necessarily nested between levels. ► Operations are performed on the representatives of the same level independently. ► Fuzzification of crisp objects/operations is unique and keep all the properties of the crisp case.
Transcription factors are proteins lying at the endpoint of signaling pathways that control the complex process of DNA transcription. Typically, they are structurally disordered in the inactive state, but in response to an external stimulus, like a suitable ligand, they change their conformation, thereby activating DNA transcription in a spatiotemporal fashion. The observed disorder or fuzziness is functionally beneficial because it can add adaptability, versatility, and reversibility to the interaction. In this context, mimetics of the basic region of the GCN4 transcription factor (Tf) and their interaction with dsDNA sequences would be suitable models to explore the concept of conformational fuzziness experimentally. Herein, we present the first example of a system that mimics the DNA sequence-specific recognition by the GCN4 Tf through the formation of a non- covalent tetra-component complex: peptide-azo beta-CyD(dimer)-peptide-DNA. The non-covalent complex is constructed on the one hand by a 30 amino acid peptide corresponding to the basic region of GCN4 and functionalized with an adamantane moiety, and on the other hand an allosteric receptor, the azoCyDdimer, that has an azobenzene linker connecting two beta-cyclodextrin units. The azoCyDdimer responds to light stimulus, existing as two photo-states: the first thermodynamically stable with an E:Z isomer ratio of 95:5 and the second obtained after irradiation with ultraviolet light, resulting in a photostationary state with a 60:40 E:Z ratio. Through electrophoretic shift assays and circular dichroism spectroscopy, we demonstrate that the E isomer is responsible for dimerization and recognition. The formation of the non-covalent tetra component complex occurs in the presence of the GCN4 cognate dsDNA sequence (' 5-..ATGA cg TCAT..-3 ') but not with (' 5-..ATGA c TCAT..-3 ') that differs in only one spacing nucleotide. Thus, we demonstrated that the tetra-component complex is formed in a specific manner that depends on the geometry of the ligand, the peptide length, and the ds DNA sequence. We hypothesized that the mechanism of interaction is sequential, and it can be described by the polymorphism model of static fuzziness. We argue that chemically modified peptides of the GCN4 Tf are suitable minimalist experimental models to investigate conformational fuzziness in protein-DNA interactions.
The first aim is to emphasize the use of fuzziness in data analysis to capture information that has been traditionally disregarded with a cost in the precision of the conclusions. Fuzziness can be considered in the data analysis process at various stages, but the main target in this paper will be fuzziness in the data. Depending on the nature of the fuzzy data or the aim to which they are handled, different approaches should be applied. We attempt to contribute to the clarification of such a difference while focusing on the so-called ontic approach in contrast to the epistemic approach. The second aim is to underline the need of considering robust methods to reduce the misleading impact of outliers in fuzzy data analysis. We propose trimming as a general and intuitive method to discard outliers. We exemplify this approach with the case of the ontic fuzzy trimmed mean/variance and highlight the differences with the epistemic case. All the discussions and developments are illustrated by means of a case-study concerning the perception of lengths of men and women.
We study the extent of quantum gravitational effects in the internal region of non-singular, Hayward-like solutions of Einstein’s field equations according to the formalism known as horizon quantum mechanics. We grant a microscopic description to the horizon by considering a huge number of soft, off-shell gravitons, which superimpose in the same quantum state, as suggested by Dvali and Gomez. In addition to that, the constituents of such a configuration are understood as loosely confined in a binding harmonic potential. A simple analysis shows that the resolution of a central singularity through quantum physics does not tarnish the classical description, which is bestowed upon this extended self-gravitating system by General Relativity. Finally, we estimate the appearance of an internal horizon as being negligible, because of the suppression of the related probability caused by the large number of virtual gravitons.
The wide usage of relational databases motivated researchers to develop more user friendly interfaces which would allow a larger population of users to access databases. Such interfaces range from visual to natural language based. This paper contributes a question driven query model which falls under the natural language based category. The proposed model supports fuzziness where every user is given the freedom to define his/her own understanding of fuzzy terms. The developed system captures the fuzzy understanding of each user to utilize it while deciding on the result to be communicated back as answer to a raised question. Data mining techniques are employed to guide users in defining their fuzzy understanding. The developed model is intended to help users to retrieve data from a relational database without expecting them to know SQL. The system handles different types of questions, including (1) simple questions, (2) complex questions with inner joins and where conditions, (3) questions that involve usage of aggregate functions (e.g., min, max, etc.), and (4) questions with fuzzy terms. The reported test results demonstrate the effectiveness and applicability of the developed system in handling various types of questions raised by a heterogeneous set of users ranging from professional to naive.