Results 81 to 90 of about 10,612,437 (315)
Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma
Molecular Oncology, EarlyView.Using cell surface proximity biotinylation, we identified tetraspanin TSPAN4 within the PD‐L1 interactome of melanoma cells. TSPAN4 negatively regulates PD‐L1 expression and lateral mobility by limiting its interaction with CMTM6 and promoting PD‐L1 degradation.
Guus A. Franken +7 more
wiley +1 more source
Dynamic prediction of gas concentration based on time series
Gong-kuang zidonghua, 2018 Existing gas concentration prediction methods could only achieve static gas concentration prediction, could not update with accumulation of gas data, as a result, the prediction results were not timeliness.
GUO Siwen, TAO Yufan, LI Chao
doaj +1 more source
Nonlinear Dynamic Boltzmann Machines for Time-Series Prediction
AAAI Conference on Artificial Intelligence, 2017 The dynamic Boltzmann machine (DyBM) has been proposed as a stochastic generative model of multi-dimensional time series, with an exact, learning rule that maximizes the log-likelihood of a given time series.
Sakyasingha Dasgupta, T. Osogami
semanticscholar +1 more source
Molecular Oncology, EarlyView.Pharmacologic ascorbate (vitamin C) increases ROS, disrupts cellular metabolism, and induces DNA damage in CRPC cells. These effects sensitize tumors to PARP inhibition, producing synergistic growth suppression with olaparib in vitro and significantly delayed tumor progression in vivo. Pyruvate rescue confirms ROS‐dependent activity.
Nicolas Gordon +13 more
wiley +1 more source
Mistuned Dynamic Response Analysis of Series Mechanism
Jixie chuandong, 2016 The series periodic mechanism has mistuned dynamic response and peculiarity. The series mechanism model is set up based on theory and method of multi- body dynamics.
Yu Linchong, Lin Zhishu, Lin Xingyan
doaj
Using Dynamics to Analyse Time Series
, 2017 We present a review of recent work to analyze time series in a robust manner using Wasserstein distances which are numerical costs of an optimal transportation problem. Given a time series, the long-term behavior of the dynamical system represented by the time series is reconstructed by Takens delay embedding method.
openaire +2 more sources
Stochastic dynamic modeling of short gene expression time-series data [PDF]
, 2008 Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Ho, DWC +5 more
core +1 more source
LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro
Molecular Oncology, EarlyView.Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix +13 more
wiley +1 more source
Dynamic parameters for Brazilian financial time series
Economia Aplicada, 2002 In this study we analyse a Brazilian stock index called IBOVESPA using techniques from dynamical systems theory and stochastic processes. We discuss the Lyapunov exponent, the correlation dimension, the LempelZiv complexity, the Hurst exponent and the ...
Gerson Francisco +2 more
doaj
Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin
Molecular Oncology, EarlyView.The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla +10 more
wiley +1 more source