Results 111 to 120 of about 1,787,003 (299)
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li +6 more
wiley +1 more source
Spectral guided sparse inverse covariance estimation of metabolic networks in Parkinson's disease. [PDF]
Spetsieris PG, Eidelberg D.
europepmc +1 more source
Multi‐trait genome‐wide association mapping identifies a central hub regulator, COLD AND CATECHINS REGULATOR 1 (CCR1), and its excellent natural allele variation, coordinately enhancing cold tolerance and promoting catechins biosyntheis. CsCCR1 interacts with CsCBF1/3 and is transcriptionally activated by CsLUX and CsKUA1 to promote catechins ...
Yanli Wang +10 more
wiley +1 more source
Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold
This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD ...
Xiaoqiang Hua +3 more
doaj +1 more source
Assessing Strengths and Limitations of Magnetoencephalography Source Imaging With Intracerebral EEG
Simultaneous MEG and stereotactic EEG (SEEG) recordings provide a direct validation framework for MEG source imaging in focal epilepsy. Virtual SEEG signals derived from MEG reconstructions reveal significant agreement with intracranial measures of spike localization, resting‐state oscillations, and functional connectivity, while also identifying ...
Jawata Afnan +10 more
wiley +1 more source
Target Detection Using Nonsingular Approximations for a Singular Covariance Matrix
Accurate covariance matrix estimation for high-dimensional data can be a difficult problem. A good approximation of the covariance matrix needs in most cases a prohibitively large number of pixels, that is, pixels from a stationary section of the image ...
Nir Gorelik +3 more
doaj +1 more source
Semiparametric estimation with missing covariates
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
A novel exercise‐inducible myokine acidic ribosomal protein P2 (RPLP2), initially identified from human trials, is presented here, whose circulating levels negatively correlate with clinical anxiety severity. Muscle‐derived RPLP2 enhances hippocampal ribosomal assembly and adult neurogenesis to rescue stress‐induced anxiety deficits.
Peiyu Luo +18 more
wiley +1 more source
StackingNet: Collective Inference Across Independent AI Foundation Models
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li +4 more
wiley +1 more source
Application of regularized covariance matrices in logistic regression and portfolio optimization
Covariance estimation has widespread applications in various fields such as logistic regression and portfolio optimization. However, in high-dimensional or small-sample scenarios, traditional covariance matrix estimation often encounters the problem of ...
Fang Sun, Xiaoqing Huang
doaj +1 more source

