Results 101 to 110 of about 576,901 (299)

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

Molecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski, Liudmyla Dolinchuk, Michał Jerzak, Albert Gandurski, Tomasz Grochowski, Weronika Wojtyś, Maciej Zadrożny, Wojciech Kaźmierczak, Małgorzata Lenarcik, Marta Matejak‐Górska, Radosław Samsel, Tomasz Olesiński, Dawid Walerych   +12 more
wiley   +1 more source

Scalable Methods for Time Series Classification

, 2023
Time series classification is a specialised area of machine learning focused on understanding and exploiting dynamic processes such as environmental, patient, and equipment monitoring, and financial markets.
ANGUS HUGH DEMPSTER (15365449)
core   +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

Automated FRAP microscopy for high‐throughput analysis of protein dynamics in chromatin organization and transcription

FEBS Open Bio, EarlyView.
RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz, Bart Geverts, Johan A. Slotman, Andrea Sacchetti, Stefan Prekovic, Martin E. van Royen, Adriaan B. Houtsmuller   +6 more
wiley   +1 more source

Optimal shapelets tree for time series interpretable classification

EURO Journal on Computational Optimization
Time series shapelets are a state-of-the-art data mining technique that is applied to time series supervised classification tasks. Shapelets are defined as subsequences that retain the most discriminating power contained in time series.
Lorenzo Bonasera, Stefano Gualandi
doaj   +1 more source

A novel uncertainty-aware liquid neural network for noise-resilient time series forecasting and classification [PDF]

While Liquid Neural Networks (LNN) are promising for modeling dynamic systems, there is no internal mechanism that quantifies the uncertainty of a prediction.
Salvi, Massimo, Akpinar, Muhammed Halil, Sengur, Abdulkadir, Atila, Orhan, Acharya, U. R., Acharya, U.R.   +5 more
core   +1 more source

Mycobacterial cell division arrest and smooth‐to‐rough envelope transition using CRISPRi‐mediated genetic repression systems

FEBS Open Bio, EarlyView.
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point, Wafaa Achache, Janïs Laudouze, Eliana Sepulveda Ramos, Mickaël Maziero, Céline Crauste, Stéphane Canaan, Pierre Santucci   +7 more
wiley   +1 more source

Multidimensional time series classification with multiple attention mechanism

Complex & Intelligent Systems
The classification of multidimensional time series holds significant importance across various domains, including action classification, medical diagnosis, and credit assessment.
Chen Liu, Zihan Wei, Lixin Zhou, Ying Shao   +3 more
doaj   +1 more source

Scalable and Explainable Time Series Classification

, 2022
© 2022 Nestor Stiven Cabello WilsonTime series data are ubiquitous, and the explosion of sensor technologies on industry applications has further accelerated their growth.
Cabello Wilson, Nestor Stiven
core  

LEVERAGING TEMPORAL SUBSEQUENCES FOR TIME-SERIES CLASSIFICATION

, 2020
Research on time-series classification has garnered importance among practitioners in the data mining community. A major reason behind the ever-increasing interest among data-miners is the plethora of time-series data available from a wide range of real ...
Roychoudhury, Shoumik
core   +1 more source