Results 61 to 70 of about 34,245 (290)

Next‐generation proteomics improves lung cancer risk prediction

Molecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Combining antibody conjugates with cytotoxic and immune‐stimulating payloads maximizes anti‐cancer activity

Molecular Oncology, EarlyView.
Methods to improve antibody–drug conjugate (ADC) treatment durability in cancer therapy are needed. We utilized ADCs and immune‐stimulating antibody conjugates (ISACs), which are made from two non‐competitive antibodies, to enhance the entry of toxic payloads into cancer cells and deliver immunostimulatory agents into immune cells.
Tiexin Wang, Dong Jun Koo, Peter M. Tessier, Greg M. Thurber   +3 more
wiley   +1 more source

Shrinkage Estimation of Linear Regression Models with ARIMA Errors and Applications to Canadian Crime Rates Data

Statistica
Shrinkage methods for estimating the parameters of a regression model with autoregressive integrated moving average (ARIMA) errors are presented when some of the regression parameters are restricted to a subspace.
Sharandeep Pandher, Shakhawat Hossain, Andrei Volodin   +2 more
doaj   +1 more source

Optimal method in multiple regression with structural changes

, 2015
In this paper, we consider an estimation problem of the regression coefficients in multiple regression models with several unknown change-points. Under some realistic assumptions, we propose a class of estimators which includes as a special cases ...
Chen, Fuqi, Nkurunziza, Sévérien
core   +1 more source

Combining Minimax Shrinkage Estimators [PDF]

Journal of the American Statistical Association, 1986
Abstract When one estimates a multivariate normal mean, the use of Stein estimation entails both the grouping of coordinates and the selection of a set of targets toward which to shrink each group. In this article we propose new minimax multiple shrinkage estimators that allow for multiple specifications of these aspects.
openaire   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Kibria–Lukman-Type Estimator for Regularization and Variable Selection with Application to Cancer Data

Mathematics, 2023
Following the idea presented with regard to the elastic-net and Liu-LASSO estimators, we proposed a new penalized estimator based on the Kibria–Lukman estimator with L1-norms to perform both regularization and variable selection.
Adewale Folaranmi Lukman, Jeza Allohibi, Segun Light Jegede, Emmanuel Taiwo Adewuyi, Segun Oke, Abdulmajeed Atiah Alharbi   +5 more
doaj   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Classic and Bayes Shrinkage Estimation in Rayleigh Distribution Using a Point Guess Based on Censored Data

پژوهش‌های ریاضی, 2018
Introduction      In classical methods of statistics, the parameter of interest is estimated based on a random sample using natural estimators such as maximum likelihood or unbiased estimators (sample information).
azadeh kiapour
doaj  

Probability Distribution of Random Ridge Factor [PDF]

المجلة العراقية للعلوم الاحصائية, 2008
In this paper, we concerned with the research about the probability distribution of random ridge factor. The estimator of regression parameter is characterized as the shrunken estimator.
doaj   +1 more source