218 research outputs found

    Perturbation Centrality and Turbine: A Novel Centrality Measure Obtained Using a Versatile Network Dynamics Tool

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    Analysis of network dynamics became a focal point to understand and predict changes of complex systems. Here we introduce Turbine, a generic framework enabling fast simulation of any algorithmically definable dynamics on very large networks. Using a perturbation transmission model inspired by communicating vessels, we define a novel centrality measure: perturbation centrality. Hubs and inter-modular nodes proved to be highly efficient in perturbation propagation. High perturbation centrality nodes of the Met-tRNA synthetase protein structure network were identified as amino acids involved in intra-protein communication by earlier studies. Changes in perturbation centralities of yeast interactome nodes upon various stresses well recapitulated the functional changes of stressed yeast cells. The novelty and usefulness of perturbation centrality was validated in several other model, biological and social networks. The Turbine software and the perturbation centrality measure may provide a large variety of novel options to assess signaling, drug action, environmental and social interventions. The Turbine algorithm is available at: http://www.turbine.linkgroup.huComment: 21 pages, 4 figues, 1 table, 58 references + a Supplement of 52 pages, 10 figures, 9 tables and 39 references; Turbine algorithm is available at: http://www.turbine.linkgroup.h

    Modularity in Protein Complex and Drug Interactions Reveals New Polypharmacological Properties

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    Recent studies have highlighted the importance of interconnectivity in a large range of molecular and human disease-related systems. Network medicine has emerged as a new paradigm to deal with complex diseases. Connections between protein complexes and key diseases have been suggested for decades. However, it was not until recently that protein complexes were identified and classified in sufficient amounts to carry out a large-scale analysis of the human protein complex system. We here present the first systematic and comprehensive set of relationships between protein complexes and associated drugs and analyzed their topological features. The network structure is characterized by a high modularity, both in the bipartite graph and in its projections, indicating that its topology is highly distinct from a random network and that it contains a rich and heterogeneous internal modular structure. To unravel the relationships between modules of protein complexes, drugs and diseases, we investigated in depth the origins of this modular structure in examples of particular diseases. This analysis unveils new associations between diseases and protein complexes and highlights the potential role of polypharmacological drugs, which target multiple cellular functions to combat complex diseases driven by gain-of-function mutations

    Network Modeling Identifies Molecular Functions Targeted by miR-204 to Suppress Head and Neck Tumor Metastasis

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    Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases

    Observation of a New Excited Beauty Strange Baryon Decaying to Ξb- π+π-

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    The Ξb-π+π- invariant mass spectrum is investigated with an event sample of proton-proton collisions at s=13 TeV, collected by the CMS experiment at the LHC in 2016-2018 and corresponding to an integrated luminosity of 140 fb-1. The ground state Ξb- is reconstructed via its decays to J/ψΞ- and J/ψΛK-. A narrow resonance, labeled Ξb(6100)-, is observed at a Ξb-π+π- invariant mass of 6100.3±0.2(stat)±0.1(syst)±0.6(Ξb-) MeV, where the last uncertainty reflects the precision of the Ξb- baryon mass. The upper limit on the Ξb(6100)- natural width is determined to be 1.9 MeV at 95% confidence level. The low Ξb(6100)- signal yield observed in data does not allow a measurement of the quantum numbers of the new state. However, following analogies with the established excited Ξc baryon states, the new Ξb(6100)- resonance and its decay sequence are consistent with the orbitally excited Ξb- baryon, with spin and parity quantum numbers JP=3/2-

    Measurement of the inclusive and differential Higgs boson production cross sections in the decay mode to a pair of τ Leptons in pp collisions at sqrt[s]=13  TeV

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    Measurements of the inclusive and differential fiducial cross sections of the Higgs boson are presented, using the τ lepton decay channel. The differential cross sections are measured as functions of the Higgs boson transverse momentum, jet multiplicity, and transverse momentum of the leading jet in the event, if any. The analysis is performed using proton-proton collision data collected with the CMS detector at the LHC at a center-of-mass energy of 13  TeV and corresponding to an integrated luminosity of 138  fb^{-1}. These are the first differential measurements of the Higgs boson cross section in the final state of two τ leptons. In final states with a large jet multiplicity or with a Lorentz-boosted Higgs boson, these measurements constitute a significant improvement over measurements performed in other final states
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