Results 31 to 40 of about 2,360,279 (321)
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 +4 more
wiley +1 more source
Multivariate analysis of soybean genotypes
Journal of Agriculture and Natural Resources, 2020 The experiments were conducted using randomized complete block design with three replications at the research field of Agriculture Botany Division, Khumaltar, Lalitpur, Nepal in 2016 and 2017 to evaluate sixteen soybean genotypes using multivariate ...
Pallavi Kumari Singh +2 more
doaj +1 more source
Scaling analysis of multivariate intermittent time series
, 2005 The scaling properties of the time series of asset prices and trading volumes of stock markets are analysed. It is shown that similarly to the asset prices, the trading volume data obey multi-scaling length-distribution of low-variability periods. In the
Ausloos +28 more
core +2 more sources
FEBS Open Bio, EarlyView.KHS‐Cnd peptide is able to impair biofilm formation and disaggregate mature biofilms in Acinetobacter baumannii clinical isolates. Differences in extracellular metabolites reflect changes in biofilm metabolism due to KHS‐Cnd treatment. Among the differentially represented extracellular metabolites upon KHS‐Cnd treatment, the significantly altered ...
Fernando Porcelli +9 more
wiley +1 more source
Regionalization of landscape pattern indices using multivariate cluster analysis [PDF]
, 2014 This project was funded by the Government of Canada through the Mountain Pine Beetle Program, a six-year, $40 million program administered by Natural Resources Canada, Canadian Forest Service.
Long, Jed Andrew +2 more
core +1 more source
Multivariate analysis in genstat
Journal of Statistical Computation and Simulation, 1978 Genstat is a general statistical language for data analysis. The facilities for multivariate and cluster analysis within the language are described as well as the many vector and matrix operations which can be used to form multivariate analysis programs. The contents of the standard macro library relevant to multivariate analysis are also discussed.
openaire +1 more source
FEBS Open Bio, EarlyView.We investigated the toxicity of 12 active compounds commonly found in herbal weight loss supplements (WLS) using human liver and colon cell models. Epigallocatechin‐3‐gallate was the only compound showing significant toxicity. Metabolic profiling revealed protein degradation, disrupted energy and lipid metabolism suggesting that the inclusion of EGCG ...
Emily C. Davies +3 more
wiley +1 more source
COSIMA data analysis using multivariate techniques [PDF]
Geoscientific Instrumentation, Methods and Data Systems, 2015 We describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections.
J. Silén +6 more
doaj +1 more source
Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits [PDF]
, 2014 A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications.
Labouriau, Rodrigo +2 more
core +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Cognitive impairment (CI) affects the quality of life in multiple sclerosis (MS). Identifying influencing factors is key to improving CI monitoring. This systematic review and meta‐analysis examines clinical and sociodemographic variables impacting the cognitive screening Symbol Digit Modalities Test (SDMT) performance across MS ...
Katalin Lugosi +8 more
wiley +1 more source