Results 131 to 140 of about 66,452 (307)
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source
The ICH E9 (R1) guidance and the related estimand framework propose to clearly define and separate the clinical question of interest formulated as estimand from the estimation method.
Christian Bartels +5 more
doaj +1 more source
Hijacked and educated by HNSCC cells, HLA‐DR+ Schwann cells lost their normal neural‐related functions but acquired immunoregulatory phenotypes to promote CD4+ T cells transform into Tregs. HLA‐DR+ Schwann cells induced a macrophage subpopulation, Il1β.
Xiaoyan Meng +7 more
wiley +1 more source
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang +8 more
wiley +1 more source
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
wiley +1 more source
Nonparametric Tests for Conditional Symmetry in Dynamic Models. [PDF]
This article proposes omnibus tests for conditional symmetry around a parametric function in a dynamic context. Conditional moments may not exist or may depend on the explanatory variables.
Delgado, Miguel A. +1 more
core
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
Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao +4 more
wiley +1 more source
[Application of conditional inference forest in time-to-event data analysis]. [PDF]
Liu Y, Kang P, Xu J, An S.
europepmc +1 more source
Adult stem cell therapy requires more than high in vitro potency. This review proposes a systems framework in which cell‐intrinsic programs, instructive microenvironmental cues, and pre‐/post‐delivery engineering are co‐designed under standardized translational rules.
Soo‐Rim Kim +2 more
wiley +1 more source

