Results 51 to 60 of about 665,812 (269)
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Tensor product random matrix theory
Physical Review ResearchThe evolution of complex correlated quantum systems such as random circuit networks is governed by the dynamical buildup of both entanglement and entropy.
Alexander Altland +2 more
doaj +1 more source
Efficiently Correcting Matrix Products [PDF]
, 2014 We study the problem of efficiently correcting an erroneous product of two \(n\times n\) matrices over a ring. We provide a randomized algorithm for correcting a matrix product with \(k\) erroneous entries running in \(\tilde{O}(\sqrt{k}n^2)\) time and a deterministic \(\tilde{O}(kn^2)\)-time algorithm for this problem (where the notation \(\tilde{O}\)
Leszek Gasieniec +2 more
openaire +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
The Product Structure of Matrix Product States under Permutations
PRX QuantumTensor network methods have proved to be highly effective in addressing a wide variety of physical scenarios, including those lacking an intrinsic one-dimensional geometry.
Marta Florido-Llinàs +5 more
doaj +1 more source
Compressing deep neural networks by matrix product operators
Physical Review Research, 2020 A deep neural network is a parametrization of a multilayer mapping of signals in terms of many alternatively arranged linear and nonlinear transformations.
Ze-Feng Gao +6 more
doaj +1 more source
Heat current in non-Markovian open systems
New Journal of Physics, 2023 We generalize time-evolving matrix product operators method to nonequilibrium quantum transport problems. The nonequilibrium current is obtained via numerical differentiation of the generating functional which is represented as a tensor network.
Ruofan Chen
doaj +1 more source
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Dense QCD2 with matrix product states
Journal of High Energy PhysicsWe study one-flavor SU(2) and SU(3) lattice QCD in (1 + 1) dimensions at zero temperature and finite density using matrix product states and the density matrix renormalization group.
Tomoya Hayata +2 more
doaj +1 more source
FEBS Letters, EarlyView.The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi +6 more
wiley +1 more source