Results 131 to 140 of about 20,295,200 (307)

Time and memory in time series analysis [PDF]

Epidemiologia e Serviços de Saúde, 2023
Flávia Reis de Andrade, José Leopoldo Ferreira Antunes   +1 more
doaj   +1 more source

Inhibition of cyclin‐dependent kinases 12/13 using CT7439 as a treatment for colorectal cancer with CDK12 upregulation

Molecular Oncology, EarlyView.
The proposed mechanism of action for the CDK12/13 inhibitor and cyclin K degrader, CT7439. CDK12/13 inhibition interrupts transcription elongation, leading to increased DNA damage that results in cell death. This agent is a potentially novel treatment option for patients with colorectal cancer. Created in BioRender. Cyclin‐dependent kinase (CDK) 12 and
Wylie K. Watlington, Divya L. Dayanidhi, Mohammad Zokaasadi, John B. Mantyh, Pelumi D. Olawuni, Gabrielle Rupprecht, Jeremy M. Force, Shannon McCall, Ashwani K. Bahl, David S. Hsu, Jason A. Somarelli   +10 more
wiley   +1 more source

In vitro and in silico modelling of ROS1‐positive non‐small cell lung cancer reveals fusion‐dependent tyrosine kinase inhibitor responses

Molecular Oncology, EarlyView.
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq, Marc Terrones, Felicia Rodrigues Fortes, Anne Schepers, Alessia Denis, Christophe Deben, Ken Op de Beeck, Guy Van Camp, Geert Vandeweyer   +8 more
wiley   +1 more source

ADTime: Adaptive Multivariate Time Series Forecasting Using LLMs

Machine Learning and Knowledge Extraction
Large language models (LLMs) have recently demonstrated notable performance, particularly in addressing the challenge of extensive data requirements when training traditional forecasting models.
Jinglei Pei, Yang Zhang, Ting Liu, Jingbin Yang, Qinghua Wu, Kang Qin   +5 more
doaj   +1 more source

Projection of time series with periodicity on a sphere

, 2008
Predicting time series necessitates choosing adequate regressors. For this purpose, prior knowledge of the data is required. By projecting the series on a low-dimensional space, the visualization of the regressors helps to extract relevant information ...
Wertz, Vincent, European Symposium on Time Series Prediction (ESTSP'08), Onclinx, Victor, Verleysen, Michel   +3 more
core  

Unlearnable Examples for Time Series

Unlearnable examples (UEs) refer to training samples modified to be unlearnable to Deep Neural Networks (DNNs). These examples are usually generated by adding error-minimizing noises that can fool a DNN model into believing that there is nothing (no error) to learn from the data.
Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey 0001   +3 more
openaire   +3 more sources

Preoperative circulating tumor cells integrated with imaging analysis for prognostic evaluation in head and neck squamous cell carcinoma

Molecular Oncology, EarlyView.
Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach, Gizem Abaci, Tom Huberty, Axel Lechner, Lukas Käsmann, Jens Ricke, Sophia Stöcklein, Martin Canis, Philipp Baumeister, Marianna Alunni‐Fabbroni   +9 more
wiley   +1 more source

A time series causal model [PDF]

Cause-effect relations are central in economic analysis. Uncovering empirical cause-effect relations is one of the main research activities of empirical economics.
Chen, Pu
core  

CEACAM1 participation in breast cancer progression

Molecular Oncology, EarlyView.
In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin, Irina Kube‐Golovin, Anatolii Romaniuk, Gunther Wennemuth   +3 more
wiley   +1 more source

Latvian GDP: The Optimal Time Series Forecasting Algorithm

In this work an algorithm is developed for finding optimal time series model for GDP forecasting. Latvian GDP data with quarterly observation frequency is taken as time series. ARMA Analysis of Latvian GDP time series is performed.
Bezručko, Aleksandrs
core