Results 41 to 50 of about 1,104,337 (260)
FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
Evaluation of changes in prediction modelling in biomedicine using systematic reviews
BMC Medical Research MethodologyThe number of prediction models proposed in the biomedical literature has been growing year on year. In the last few years there has been an increasing attention to the changes occurring in the prediction modeling landscape.
Lara Lusa +6 more
doaj +1 more source
PICALM::MLLT10 translocated leukemia
FEBS Letters, EarlyView.This comprehensive review of PICALM::MLLT10 translocated acute leukemia provides an in‐depth review of the structure and function of CALM, AF10, and the fusion oncoprotein (1). The multifaceted molecular mechanisms of oncogenesis, including nucleocytoplasmic shuttling (2), epigenetic modifications (3), and disruption of endocytosis (4), are then ...
John M. Cullen +7 more
wiley +1 more source
Privacy-Preserving Data Sharing in High Dimensional Regression and Classification Settings
The Journal of Privacy and Confidentiality, 2012 We focus on the problem of multi-party data sharing in high dimensional data settings where the number of measured features (or the dimension) p is frequently much larger than the number of subjects (or the sample size) n, the so-called p >> n scenario ...
Stephen E. Fienberg, Jiashun Jin
doaj +1 more source
Machine learning of high dimensional data on a noisy quantum processor
npj Quantum Information, 2021 Quantum kernel methods show promise for accelerating data analysis by efficiently learning relationships between input data points that have been encoded into an exponentially large Hilbert space.
Evan Peters +8 more
doaj +1 more source
Fitting High-Dimensional Copulae to Data [PDF]
, 2011 This paper make an overview of the copula theory from a practical side. We consider different methods of copula estimation and different Goodness-of-Fit tests for model selection. In the GoF section we apply Kolmogorov-Smirnov and Cramer-von-Mises type tests and calculate power of these tests under different assumptions.
openaire +4 more sources
FEBS Letters, EarlyView.Bone metastasis in prostate cancer (PCa) patients is a clinical hurdle due to the poor understanding of the supportive bone microenvironment. Here, we identify stearoyl‐CoA desaturase (SCD) as a tumor‐promoting enzyme and potential therapeutic target in bone metastatic PCa.
Alexis Wilson +7 more
wiley +1 more source
Correlation based feature selection with clustering for high dimensional data
Journal of Electrical Systems and Information Technology, 2018 Feature selection is an essential technique to reduce the dimensionality problem in data mining task. Traditional feature selection algorithms are fail to scale on large space.
Smita Chormunge, Sudarson Jena
doaj +1 more source
Stable ant‐antlion optimiser for feature selection on high‐dimensional data
Electronics Letters, 2021 High‐dimensional data exists widely in the real world, such as gene, magnetic resonance imaging (MRI), text, web data and so on. Feature selection is an effective and powerful method that is often adopted to reduce dimensions of high‐dimensional data for
Mengmeng Li +5 more
doaj +1 more source
OUTLIER DETECTION ON HIGH DIMENSIONAL DATA USING MINIMUM VECTOR VARIANCE (MVV)
Barekeng, 2022 High-dimensional data can occur in actual cases where the variable p is larger than the number of observations n. The problem that often occurs when adding data dimensions indicates that the data points will approach an outlier.
Andi Harismahyanti A. +3 more
doaj +1 more source