Results 71 to 80 of about 1,819,138 (329)
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
, 2023 Identifying the main features and learning the causal relationships of a dynamic system from time-series of sensor data are key problems in many real-world robot applications.
N. Bellotto +7 more
core
Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach
Journal of Geophysical Research: Machine Learning and ComputationCausal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science.
J. Jake Nichol +5 more
doaj +1 more source
Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?
FEBS Letters, EarlyView.This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes +3 more
wiley +1 more source
Entropy-Based Discovery of Summary Causal Graphs in Time Series
Entropy, 2022 This study addresses the problem of learning a summary causal graph on time series with potentially different sampling rates. To do so, we first propose a new causal temporal mutual information measure for time series.
Charles K. Assaad +2 more
doaj +1 more source
Protein pyrophosphorylation by inositol pyrophosphates — detection, function, and regulation
FEBS Letters, EarlyView.Protein pyrophosphorylation is an unusual signaling mechanism that was discovered two decades ago. It can be driven by inositol pyrophosphate messengers and influences various cellular processes. Herein, we summarize the research progress and challenges of this field, covering pathways found to be regulated by this posttranslational modification as ...
Sarah Lampe +3 more
wiley +1 more source
Are causal analysis and system analysis compatible approaches? [PDF]
, 2009 In social science, one objection to causal analysis is that the assumption of the closure of the system makes it too narrow in scope, that is it only considers ‘closed’ and ‘hermetic’ systems thus neglecting many other external influences.
Russo, Federica
core +1 more source
Comparing Causal Bayesian Networks Estimated from Data
EntropyThe knowledge of the causal mechanisms underlying one single system may not be sufficient to answer certain questions. One can gain additional insights from comparing and contrasting the causal mechanisms underlying multiple systems and uncovering ...
Sisi Ma, Roshan Tourani
doaj +1 more source
FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
The causal manipulation and Bayesian estimation of chain event graphs [PDF]
, 2005 Discrete Bayesian Networks (BNs) have been very successful as a framework both for inference and for expressing certain causal hypotheses. In this paper we present a class of graphical models called the chain event graph (CEG) models, that generalises ...
Riccomagno, Eva, Smith, J. Q.
core
Causal Discovery Methods for Functional Performance of Evapotranspiration Models
Water Resources ResearchEvapotranspiration (ET) plays a key role in agricultural water resources management. However, it is challenging to predict as it is driven by water and energy availability as well as soil, vegetation, and meteorological factors, and models vary widely in
Jiaze Cao +2 more
doaj +1 more source