Long-term neural and physiological phenotyping of a single human
RA Poldrack, TO Laumann, O Koyejo, B Gregory… - Nature …, 2015 - nature.com
Psychiatric disorders are characterized by major fluctuations in psychological function over
the course of weeks and months, but the dynamic characteristics of brain function over this …
the course of weeks and months, but the dynamic characteristics of brain function over this …
ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks
Motivation Contact-map of a protein sequence dictates the global topology of structural fold.
Accurate prediction of the contact-map is thus essential to protein 3D structure prediction …
Accurate prediction of the contact-map is thus essential to protein 3D structure prediction …
On nonregularized estimation of psychological networks
An important goal for psychological science is developing methods to characterize
relationships between variables. Customary approaches use structural equation models to …
relationships between variables. Customary approaches use structural equation models to …
Estimation of covariance and precision matrix, network structure, and a view toward systems biology
MO Kuismin, MJ Sillanpää - Wiley Interdisciplinary Reviews …, 2017 - Wiley Online Library
Covariance matrix and its inverse, known as the precision matrix, have many applications in
multivariate analysis because their elements can exhibit the variance, correlation …
multivariate analysis because their elements can exhibit the variance, correlation …
An overview of large‐dimensional covariance and precision matrix estimators with applications in chemometrics
The covariance matrix (or its inverse, the precision matrix) is central to many chemometric
techniques. Traditional sample estimators perform poorly for high‐dimensional data such as …
techniques. Traditional sample estimators perform poorly for high‐dimensional data such as …
A penalized likelihood framework for high-dimensional phylogenetic comparative methods and an application to new-world monkeys brain evolution
Working with high-dimensional phylogenetic comparative data sets is challenging because
likelihood-based multivariate methods suffer from low statistical performances as the …
likelihood-based multivariate methods suffer from low statistical performances as the …
Reliable phylogenetic regressions for multivariate comparative data: illustration with the MANOVA and application to the effect of diet on mandible morphology in …
Understanding what shapes species phenotypes over macroevolutionary timescales from
comparative data often requires studying the relationship between phenotypes and putative …
comparative data often requires studying the relationship between phenotypes and putative …
[HTML][HTML] Multi-source remote sensing recognition of plant communities at the reach scale of the Vistula River, Poland
The seasonal occurrence of plant communities in rivers' reaches has a direct impact on the
flow resistance and sediment dynamics. Monitoring the occurrence of plant communities and …
flow resistance and sediment dynamics. Monitoring the occurrence of plant communities and …
Control charts for variability monitoring in high-dimensional processes
Monitoring process variability is associated with detecting changes in the covariance matrix
of a multivariate normal process. Most monitoring methods estimate the sample covariance …
of a multivariate normal process. Most monitoring methods estimate the sample covariance …
Psychoneurological symptoms and biomarkers of stress and inflammation in newly diagnosed head and neck cancer patients: a network analysis
AMM Santoso, F Jansen, CFW Peeters… - Current …, 2022 - mdpi.com
Psychoneurological symptoms are commonly reported by newly diagnosed head and neck
cancer (HNC) patients, yet there is limited research on the associations of these symptoms …
cancer (HNC) patients, yet there is limited research on the associations of these symptoms …