University of Notre Dame

About: University of Notre Dame is a education organization based out in Notre Dame, Indiana, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 22238 authors who have published 55201 publications receiving 2032925 citations. The organization is also known as: University of Notre Dame du Lac & University of Notre Dame, South Bend.

Selective inhibition of BET bromodomains.

Abstract: Epigenetic proteins are intently pursued targets in ligand discovery. So far, successful efforts have been limited to chromatin modifying enzymes, or so-called epigenetic 'writers' and 'erasers'. Potent inhibitors of histone binding modules have not yet been described. Here we report a cell-permeable small molecule (JQ1) that binds competitively to acetyl-lysine recognition motifs, or bromodomains. High potency and specificity towards a subset of human bromodomains is explained by co-crystal structures with bromodomain and extra-terminal (BET) family member BRD4, revealing excellent shape complementarity with the acetyl-lysine binding cavity. Recurrent translocation of BRD4 is observed in a genetically-defined, incurable subtype of human squamous carcinoma. Competitive binding by JQ1 displaces the BRD4 fusion oncoprotein from chromatin, prompting squamous differentiation and specific antiproliferative effects in BRD4-dependent cell lines and patient-derived xenograft models. These data establish proof-of-concept for targeting protein-protein interactions of epigenetic 'readers', and provide a versatile chemical scaffold for the development of chemical probes more broadly throughout the bromodomain family.

The Population Biology of Invasive Species

Abstract: ■ Abstract Contributions from the field of population biology hold promise for understanding and managing invasiveness; invasive species also offer excellent opportunities to study basic processes in population biology. Life history studies and demographic models may be valuable for examining the introduction of invasive species and identifying life history stages where management will be most effective. Evolutionary processes may be key features in determining whether invasive species establish and spread. Studies of genetic diversity and evolutionary changes should be useful for

The human disease network

Abstract: A network of disorders and disease genes linked by known disorder-gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.

Review of Particle Physics

Abstract: This biennial Review summarizes much of particle physics. Using data from previous editions, plus 2158 new measurements from 551 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We also summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. Among the 108 reviews are many that are new or heavily revised including those on neutrino mass, mixing, and oscillations, QCD, top quark, CKM quark-mixing matrix, V-ud & V-us, V-cb & V-ub, fragmentation functions, particle detectors for accelerator and non-accelerator physics, magnetic monopoles, cosmological parameters, and big bang cosmology.

The structure and dynamics of networks

Abstract: Networks have become a general concept to model the structure of arbitrary relationships among entities. The framework of a network introduces a fundamentally new approach apart from ‘classical’ structures found in physics to model the topology of a system. In the context of networks fundamentally new topological effects can emerge and lead to a class of topologies which are termed ‘complex networks’. The concept of a network successfully models the static topology of an empirical system, an arbitrary model, and a physical system. Generally networks serve as a host for some dynamics running on it in order to fulfill a function. The question of the reciprocal relationship among a dynamical process on a network and its topology is the context of this Thesis. This context is studied in both directions. The network topology constrains or enhances the dynamics running on it, while the reciprocal interaction is of the same importance. Networks are commonly the result of an evolutionary process, e.g. protein interaction networks from biology. Within such an evolution the dynamics shapes the underlying network topology with respect to an optimal achievement of the function to perform. Answering the question what the influence on a dynamics of a particular topological property has requires the accurate control over the topological properties in question. In this Thesis the degree distribution, twopoint correlations, and clustering are the studied topological properties. These are motivated by the ubiquitous presence and importance within almost all empirical networks. An analytical framework to measure and to control such quantities of networks along with numerical algorithms to generate them is developed in a first step. Networks with the examined topological properties are then used to reveal their impact on two rather general dynamics on networks. Finally, an evolution of networks is studied to shed light on the influence the dynamics has on the network topology.