Results 51 to 60 of about 4,938,948 (296)
Universal Features of Network Topology [PDF]
, 2004 Recent studies have revealed characteristic general features in the topology of real-world networks. We investigate the universality of mechanisms that result in the power-law behaviour of many real-world networks, paying particular attention to the Barabasi-Albert process of preferential attachment as the most successful.
Austin, K, Rodgers, GJ
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Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
FEBS Letters, EarlyView.EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Strongly Uncontrollable Network Topologies [PDF]
IEEE Transactions on Control of Network Systems, 2020 In this paper, we present a class of network topologies under which the Laplacian consensus dynamics exhibits undesirable controllability properties under a broadcast control signal. Specifically, the networks we characterize are uncontrollable for any subset of the nodes chosen as control inputs and that emit a common control signal.
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Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
FEBS Letters, EarlyView.How do genomes gain new functional parts? In eukaryotes, which tend to evolve under weak selection, much of the genome is junk. Palazzo and Qiu borrow the logic of Markov chains to show how non‐functional DNA becomes functional through the appearance of intermediate states, which arise due to epistasis, buffering, and biochemical messiness, allowing ...
Alexander F. Palazzo, Yi Qiu
wiley +1 more source
Determination of the topology of a directed network [PDF]
Proceedings 16th International Parallel and Distributed Processing Symposium, 2002 We consider strongly-connected directed networks of identical synchronous, finite-state processors with in- and out-degree uniformly bounded by a network constant. Via a straightforward extension of Ostrovsky and Wilkerson's Backwards Communication Algorithm in [OW], we exhibit a protocol which solves the Global Topology Determination Problem, the ...
openaire +5 more sources
On equivalence between network topologies [PDF]
2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2010 8 pages, 12 figures, 48th Annual Allerton Conference on Communication, Control, and Computing ...
Tracey Ho +2 more
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Incremental On-line Clustering with a Topology-Learning Hierarchical ART Neural Network Using Hyperspherical Categories [PDF]
, 2012 Tscherepanow M. Incremental On-line Clustering with a Topology-Learning Hierarchical ART Neural Network Using Hyperspherical Categories. In: Perner P, ed. Poster and Industry Proceedings of the Industrial Conference on Data Mining (ICDM).
Perner, Petra, Tscherepanow, Marko
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FEBS Letters, EarlyView.Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana +3 more
wiley +1 more source
Episodic Clustering of Data Streams Using a Topology-Learning Neural Network [PDF]
, 2012 Tscherepanow M, Kühnel S, Riechers S. Episodic Clustering of Data Streams Using a Topology-Learning Neural Network. In: Lemaire V, Lamirel J-C, Cuxac P, eds. Proceedings of the ECAI Workshop on Active and Incremental Learning (AIL).
Lamirel, Jean-Charles +5 more
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