Results 91 to 100 of about 50,616 (261)
Advanced Science, EarlyView.Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi +7 more
wiley +1 more source
Hierarchical Bayesian models of transcriptional and translational regulation processes with delays. [PDF]
Bioinformatics, 2021 Cortez MJ +4 more
europepmc +1 more source
Advanced Science, EarlyView.Through integrated proteomic and metabolomic profiling, Zhao et al. identified three molecular subtypes of high‐grade serous ovarian cancer. The high‐risk subtype exhibits activated arachidonic acid metabolism and cyclooxygenase‐2 overexpression. This metabolic axis promotes M2‐like macrophage infiltration, which contributes to platinum resistance ...
Yuxi Zhao +11 more
wiley +1 more source
Principled Decision-Making Workflow with Hierarchical Bayesian Models of High-Throughput Dose-Response Measurements. [PDF]
Entropy (Basel), 2021 Ma EJ, Kummer A.
europepmc +1 more source
Advanced Science, EarlyView.Computational simulations of tumor evolution are increasingly used to infer the rules underlying cancer growth, with the goal of one day recommending tailored treatments. Here we show that the properties of lung cancer sequencing data are best replicated by a model which assumes that cells compete both to proliferate and survive. ABSTRACT Computational
Helena Coggan +5 more
wiley +1 more source
Advanced Science, EarlyView.TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao +8 more
wiley +1 more source
Modeling Player Engagement with Bayesian Hierarchical Models
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2018 Modeling player engagement is a key challenge in games. However, the gameplay signatures of engaged players can be highly context-sensitive, varying based on where the game is used or what population of players is using it. Traditionally, models of player engagement are investigated in a particular context, and it is unclear how ...
Sawyer, Robert +3 more
openaire +2 more sources
Advanced Science, EarlyView.A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen +5 more
wiley +1 more source
Bayesian Hierarchical Tobit Models: an application to travel distance analysis
Ingeniería, 2017 The objective of travel distance models is to better understand travel behavior so that policies can be implemented for reducing travel and with that the externalities of transport such as air pollution, congestion, and crashes.
Jonathan Aguero-Valverde
doaj +1 more source
Advanced Science, EarlyView.This review explores emerging 2D materials beyond graphene, including graphdiyne, phosphorene, borophene, siloxene, MBene, antimonene, and germanene for Li/Na–S batteries. It analyzes their roles as sulfur hosts, metallic anode protectors, separators, and electrolyte fillers, emphasizing polysulfide suppression, dendrite inhibition, and interfacial ...
Naveen Kumar T. R +7 more
wiley +1 more source