Results 81 to 90 of about 2,287,103 (299)
Spherical Regression with Errors in Variables
The Annals of Statistics, 1989 Suppose \(u_ 1,...,u_ n\), \(v_ 1,...,v_ n\) are random points on the sphere such that for unknown points \(\xi_ 1,...,\xi_ n\) and unknown rotation \(A_ 0\), the distribution of \(u_ i\) depends only on \(u^ t_ i\xi_ i\) and that of \(v_ i\) on \(v^ t_ iA_ 0\xi_ i\).
openaire +2 more sources
Molecular Oncology, EarlyView.This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan +9 more
wiley +1 more source
Algorithms and statistical analysis for linear structured weighted total least squares problem
Geodesy and GeodynamicsWeighted total least squares (WTLS) have been regarded as the standard tool for the errors-in-variables (EIV) model in which all the elements in the observation vector and the coefficient matrix are contaminated with random errors.
Jian Xie +4 more
doaj +1 more source
Errors-in-variables and validation problems in reaction norm predictions for wild populations [PDF]
Modeling, Identification and ControlStudies of phenotypic responses in wild populations are often based on reaction norm models where the environmental drivers in many cases are related to climate change.
Rolf Ergon
doaj +1 more source
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Molecular Oncology, EarlyView.Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts +8 more
wiley +1 more source
Spatial‐statistical downscaling with uncertainty quantification in biodiversity modelling
Methods in Ecology and EvolutionAccurate downscaling with uncertainty quantification and its inclusion in fitting biodiversity models to data are essential for accurate, valid inferences and predictions.
Xiaotian Zheng +4 more
doaj +1 more source
Molecular Oncology, EarlyView.A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira +14 more
wiley +1 more source
Molecular Oncology, EarlyView.This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian +10 more
wiley +1 more source
Accruals, Investment and Errors-in-Variables [PDF]
We formulate well-known discretionary accruals models in an investment setting. Given that accruals basically consist of short-term investment, we introduce, (i) cash-flows, as a proxy for financial constraints and other financial markets imperfections ...
Christian Calmès +3 more
core
Molecular Oncology, EarlyView.A comprehensive genomic and proteomic analysis of cervical cancer revealed STK11 and STX3 as a potential biomarkers of chemoradiation resistance. Our study demonstrated EGFR as a therapeutic target, paving the way for precision strategies to overcome treatment failure and the DNA repair pathway as a critical mechanism of resistance.
Janani Sambath +13 more
wiley +1 more source