Results 91 to 100 of about 139,695 (308)

Proximities in dimensionality reduction

, 2022
International audienceDimensionality reduction aims at representing high-dimensional data in a lower-dimensional representation, while preserving their structure (clusters, outliers, manifold).
Journaux, Ludovic, De Bodt, Cyril, Sautot, Lucile, Bodt De, Cyril, Lee, John Aldo   +4 more
core   +1 more source

USP29‐regulated noncanonical stabilization of the hypoxia‐inducible factor‐α in aggressive prostate cancer

Molecular Oncology, EarlyView.
We identify USP29 as the only DUB mirroring CA9 expression, a marker of hypoxia and HIF pathway activation associated with PCA aggressiveness. USP29 stabilizes HIF‐1α and HIF‐2α via a noncanonical mechanism that is independent of PHD/pVHL activity yet relies on proteasomal regulation, establishing USP29 as a previously unrecognized regulator of hypoxic
Amelie S Schober, Leire Moreno‐Cugnon, Laura Martínez‐Pérez, Amaia Ercilla, Amaia Zabala‐Letona, Adrián Vicente‐Barrueco, Maider Fagoaga‐Eugui, Saioa Garcia‐Longarte, Blanca Calle‐Ciborro, Encarnación Pérez‐Andrés, Onintza Carlevaris, Sara Pozo, Isabel Mendizabal, Ugo Mayor, Arkaitz Carracedo, Violaine Sée, Edurne Berra   +16 more
wiley   +1 more source

Optimal Dimensionality Reduction using Conditional Variational AutoEncoder

Transactions on Cryptographic Hardware and Embedded Systems
The benefits of using Deep Learning techniques to enhance side-channel attacks performances have been demonstrated over recent years. Most of the work carried out since then focuses on discriminative models.
Sana Boussam, Mathieu Carbone, Benoît Gérard, Guénaël Renault, Gabriel Zaid   +4 more
doaj   +1 more source

A novel quinazolinone insulin receptor inhibitor and its synergy with an EGFR inhibitor in glucose‐driven glioblastoma

Molecular Oncology, EarlyView.
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka, Wioleta Cieślik, Wojciech Płaziński, Katarzyna Stępnik, Anna Boguszewska‐Czubara, Elżbieta Kot, Robert Musioł, Mateusz Jasica, Anna Mrozek‐Wilczkiewicz, Katarzyna Malarz   +9 more
wiley   +1 more source

Robust dimensionality reduction for interferometric imaging of Cygnus A [PDF]

Extremely high data rates expected in next-generation radio interferometers necessitate a fast and robust way to process measurements in a big data context.
Thiran, Jean-Philippe, Dabbech, Arwa, Kartik, Vijay, Wiaux, Yves   +3 more
core  

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

Multi-Instance Dimensionality Reduction

, 2010
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step for high-dimensional data analysis and has been studied for years.
Sun, Yu-Yin, Ng, Michael, Zhou, Zhi-Hua
core   +2 more sources

Loss of proton‐sensing TDAG8 increases tumor progression in mouse models of colon cancer

Molecular Oncology, EarlyView.
Loss of the pH‐sensing receptor TDAG8 accelerates colorectal cancer progression in mice. Animals lacking TDAG8 expression had increased tumor growth, DNA damage, and recruitment of tumor‐associated immune cells, including macrophages, neutrophils, and monocytes.
Ermanno Malagola, Yasmine Illi, Anna Bircher, Marijn Wilmink, Rachele F. Malagutti, Solenn Ottié, Cordelia Schuler, Pedro A. Ruiz, Cheryl de Vallière, Klaus Seuwen, Gerhard Rogler, Martin Hausmann   +11 more
wiley   +1 more source

Nonlinear Dynamic Field Embedding: On Hyperspectral Scene Visualization

, 2012
In many areas of research, complex signals are commonly represented by high dimensional feature vectors. However, high dimensional vectors are difficult to analyze and interpret due to the curse of dimensionality.
Lunga, Dalton, Erosy, Okan
core  

Dimensionality reduction methods.

, 2019
Dimensionality reduction methods.
Susan Holmes (243177), Lan Huong Nguyen (2883329)   +1 more
core   +1 more source