Results 51 to 60 of about 3,165,100 (264)
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
The element-wise weighted total least squares problem
, 2006 A new technique for parameter estimation is considered in a linear measurement error model AX approx B, A = A0 + tilde A, B = B0 + tilde B, with row-wise independent and non-identically distributed measurement errors tilde A, tilde B.
Premoli, P. +3 more
core +1 more source
Coupled Least Squares Support Vector Ensemble Machines
Information, 2019 The least squares support vector method is a popular data-driven modeling method which shows better performance and has been successfully applied in a wide range of applications.
Dickson Keddy Wornyo, Xiang-Jun Shen
doaj +1 more source
Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization
Molecular Oncology, EarlyView.In the current study, we demonstrate that the oncogene DMTF1β regulates ULK1 stability by reducing its proteasomal degradation in cancer cells. This stabilization enables ULK1 to induce autophagy, which in turn facilitates cancer cell migration. Consequently, reduced DMTF1β levels lead to decreased autophagy and impaired cancer cell migration.
Jun Xu +13 more
wiley +1 more source
On the complex least squares problem with constrained phase [PDF]
, 2011 The problem of solving approximately in the least squares sense an overdetermined linear system of equations with complex valued coefficients is considered, where the elements of the solution vector are constrained to have the same phase.
Markovsky, Ivan
core +2 more sources
Marginal Screening for Partial Least Squares Regression
IEEE Access, 2017 Partial least squares (PLS) regression is a versatile modeling approach for high-dimensional data analysis. Recently, PLS-based variable selection has attracted great attention due to high-throughput data reduction and modeling interpretability.
Naifei Zhao, Qingsong Xu, Hong Wang
doaj +1 more source
New Developments in Sparse PLS Regression
Frontiers in Applied Mathematics and Statistics, 2021 Methods based on partial least squares (PLS) regression, which has recently gained much attention in the analysis of high-dimensional genomic datasets, have been developed since the early 2000s for performing variable selection.
Jérémy Magnanensi +6 more
doaj +1 more source
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 +8 more
wiley +1 more source
LEAST SQUARES MULTI-WINDOW EVOLUTIONARY SPECTRAL ESTIMATION
Electrica, 2003 We present a multi-window method for obtaining the time-frequency spectrum of non-stationary signals such as speech and music. This method is based on optimal combination of evolutionary spectra that are calculated by using multi-window Gabor expansion ...
Mahmut YALÇIN, Aydın AKAN
doaj +2 more sources
A novel interpretation of least squares solution
International Journal of Mathematics and Mathematical Sciences, 1992 We show that the well-known least squares (LS) solution of an overdetermined system of linear equations is a convex combination of all the non-trivial solutions weighed by the squares of the corresponding denominator determinants of the Cramer's rule ...
Jack-Kang Chan
doaj +1 more source