Results 101 to 110 of about 1,988,912 (333)

Reduction of Dimensionality for Classification

, 2017
We present an algorithm for the reduction of dimensionality useful in statistical classification problems where observations from two multivariate normal distributions are discriminated. It is based on Principal Components Analysis and consists of a simultaneous diagonalization of two covariance matrices.
Cuevas Covarrubias,C, RICCOMAGNO, EVA
openaire   +3 more sources

Dimensionality Reduction with Image Data [PDF]

, 2004
A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We propose a new method based on the projection of the images as matrices after a Procrustes rotation and show that it leads to a better reconstruction of images.
Peña, Daniel, Benito, Mónica
openaire   +4 more sources

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Escape from TGF‐β‐induced senescence promotes aggressive hallmarks in epithelial hepatocellular carcinoma cells

Molecular Oncology, EarlyView.
Chronic TGF‐β exposure drives epithelial HCC cells from a senescent state to a TGF‐β resistant mesenchymal phenotype. This transition is characterized by the loss of Smad3‐mediated signaling, escape from senescence, enhanced invasiveness and metastatic potential, and upregulation of key resistance modulators such as MARK1 and GRM8, ultimately promoting
Minenur Kalyoncu, Dilara Demirci, Sude Eris, Bengisu Dayanc, Ece Cakiroglu, Merve Basol, Merve Uysal, Gulcin Cakan‐Akdogan, Fang Liu, Mehmet Ozturk, Gökhan Karakülah, Serif Senturk   +11 more
wiley   +1 more source

Practical challenges in data‐driven interpolation: Dealing with noise, enforcing stability, and computing realizations

International Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley   +1 more source

Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders

Applied Sciences
The machine learning-based approaches for analysing the mobility needs of users are currently the most prevalent approach in the mobility-on-demand (MoD) analysis.
Martin Gregurić, Filip Vrbanić, Edouard Ivanjko   +2 more
doaj   +1 more source

ShcD adaptor protein drives invasion of triple negative breast cancer cells by aberrant activation of EGFR signaling

Molecular Oncology, EarlyView.
We identified adaptor protein ShcD as upregulated in triple‐negative breast cancer and found its expression to be correlated with reduced patient survival and increased invasion in cell models. Using a proteomic screen, we identified novel ShcD binding partners involved in EGFR signaling pathways.
Hayley R. Lau, Hayley S. Smith, Begüm Alural, Claire E. Martin, Laura A. New, Manali Tilak, Sara L. Banerjee, Hannah N. Robeson, Nicolas Bisson, Anne‐Claude Gingras, Jasmin Lalonde, Nina Jones   +11 more
wiley   +1 more source

Data‐driven performance metrics for neural network learning

International Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri, Mauro Gaggero, Marcello Sanguineti   +2 more
wiley   +1 more source

Reduction of infinite dimensional equations

Electronic Journal of Differential Equations, 2006
In this paper, we use the general Legendre transformation to show the infinite dimensional integrable equations can be reduced to a finite dimensional integrable Hamiltonian system on an invariant set under the flow of the integrable equations.
Zhongding Li, Taixi Xu
doaj  

Inhibitor of DNA binding‐1 is a key regulator of cancer cell vasculogenic mimicry

Molecular Oncology, EarlyView.
Elevated expression of transcriptional regulator inhibitor of DNA binding 1 (ID1) promoted cancer cell‐mediated vasculogenic mimicry (VM) through regulation of pro‐angiogenic and pro‐cancerous genes (e.g. VE‐cadherin (CDH5), TIE2, MMP9, DKK1). Higher ID1 expression also increased metastases to the lung and the liver.
Emma J. Thompson, Emma L. Dorward, Kristyn Jurrius, Nathalie Nataren, Markus Tondl, Kay K. Myo Min, Michaelia P. Cockshell, Anahita Fouladzadeh, John Toubia, Mark DeNichilo, Delphine Merino, Claudine S. Bonder   +11 more
wiley   +1 more source