Results 141 to 150 of about 3,120,690 (293)
Advanced Science, EarlyView.Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais +32 more
wiley +1 more source
Cancer‐Associated BCL‐2 Mutants Reveal Mechanisms Towards Venetoclax Resistance
Advanced Science, EarlyView.Venetoclax (VEN) resistance in chronic lymphocytic leukemia arises from diverse BCL2 mutations. We map mechanisms contributing to VEN resistance across common BCL‐2 variants. G101V and D103Y reduce drug binding and increase sequestration of pro‐apoptotic proteins. V156D blocks VEN allosterically.
Jonas Aufdermauer +9 more
wiley +1 more source
Transposable Element–Driven PIEZO Mutation Enhances Locust Flight in Plateau Hypoxia
Advanced Science, EarlyView.Why transposable elements (TEs) persisted or expanded in genomes remains a mystery. Using integrated analysis of TE macro‐ and microevolution in locusts, our results showed that thousands of TE insertions promoted widespread adaptive variation. Subfamilies of candidate adaptive TEs amplified and reshaped species‐level genomic architecture.
Xuanzhao Li +8 more
wiley +1 more source
Learning Bayesian Networks with the bnlearn R Package [PDF]
bnlearn is an R package (R Development Core Team 2010) which includes several algorithms for learning the structure of Bayesian networks with either discrete or continuous variables.
Marco Scutari
core
Bayesian Networks and the Problem of Unreliable Instruments [PDF]
, 2000 We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments.
Bovens, Luc, Hartmann, Stephan
core
, 2017 Bayesian networks have grown to become a dominant type of model within the domain of probabilistic graphical models. Not only do they empower users with a graphical means for describing the relationships among random variables, but they also allow for (potentially) fewer parameters to estimate, and enable more efficient inference.
openaire +2 more sources
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
Improved risk analysis for large projects: Bayesian networks approach [PDF]
, 2010 PhDGenerally risk is seen as an abstract concept which is difficult to measure. In this thesis, we consider quantification in the broader sense by measuring risk in the context of large projects.
Fineman, Milijana
core +1 more source
Advanced Science, EarlyView.Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Renjian Li +11 more
wiley +1 more source
Spatial Bayesian neural networks
Spatial Statistics35 pages, 21 ...
Andrew Zammit-Mangion +4 more
openaire +4 more sources