Results 81 to 90 of about 4,092,880 (310)
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Time Series Clustering from High Dimensional Data
, 2015 Due to technological advances there is the possibility to col- lect datasets of growing size and dimension. On the other hand, standard techniques do not allow the easy management of large dimensional data and new techniques need to be considered in ...
DRAGO, CARLO +3 more
core +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
FEBS Letters, EarlyView.Protein aggregates threaten proteostasis and cell health. In human cells, Hsp70–J‐domain protein‐based disaggregases remove aggregates, but how they assemble remains unclear. Our biochemical findings show that DNAJA2‐ and DNAJB1‐containing disaggregase scaffolds enhance luciferase aggregate targeting, and that Hsp70 recruitment by both J‐domain ...
Anna Szlachcic, Nadinath B. Nillegoda
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
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
Journal of the National Science Foundation of Sri Lanka, 2016 This paper provides a brief introduction to high-dimensional data, a form of ‘Big Data’, and gives an overview of several data analysis concepts and techniques that could be used to explore and analyse such data. An example that involves genomics data from several Sri Lankan and United Kingdom oral cancer patients is used to illustrate the methods.
Dhammika Amaratunga, Javier Cabrera
openaire +2 more sources
Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers
Molecular Oncology, EarlyView.This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel +6 more
wiley +1 more source