Results 61 to 70 of about 644,547 (283)

Actual Causation in CP-logic

, 2011
Given a causal model of some domain and a particular story that has taken place in this domain, the problem of actual causation is deciding which of the possible causes for some effect actually caused it.
Hall, JOOST VENNEKENS, Pearl, Riguzzi, Riguzzi, Shafer, Vennekens   +6 more
core   +1 more source

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

FEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel, Carl P. O. Helmer, Shani Zev, Ronja Driller, Emily Buhr, Markus Reinbold, Renana Schwartz, Gabriel Foley, Mikael Boden, Daniel Garbe, Gerhard Schenk, Dan Thomas Major, Bernhard Loll, Thomas Brück   +13 more
wiley   +1 more source

Identification of causal intervention effects under contagion

Journal of Causal Inference, 2021
Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment – such as a vaccine – given to one individual may affect the infection outcomes of others. Epidemiologists have proposed
Cai Xiaoxuan, Loh Wen Wei, Crawford Forrest W.   +2 more
doaj   +1 more source

A Distinction between Causal Effects in Structural and Rubin Causal Models [PDF]

SSRN Electronic Journal, 2015
Structural Causal Models define causal effects in terms of a single Data Generating Process (DGP), and the Rubin Causal Model defines causal effects in terms of a model that can represent counterfactuals from many DGPs. Under these different definitions, notationally similar causal effects make distinct claims about the results of interventions to the ...
openaire   +1 more source

Latent tree models

, 2017
Latent tree models are graphical models defined on trees, in which only a subset of variables is observed. They were first discussed by Judea Pearl as tree-decomposable distributions to generalise star-decomposable distributions such as the latent class ...
Zwiernik, Piotr
core   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

FEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura, Shin‐ichi Tate, Kyota Yasuda   +2 more
wiley   +1 more source

Wine quality analysis by the structural causal model (SCM)

Croatian Journal of Food Science and Technology, 2023
Bayes network modelling for structural causal analysis between wine physicochemical data and quantitative human quality blind assessments is applied. The large dataset of white and red "Vinho Verde'' wine samples from Portugal, which was available from ...
Želimir Kurtanjek
doaj  

Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations

, 2015
We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations which can be ...
Fukumizu, K., Harmeling, S., Muandet, K., Peters, J., Schölkopf, B.   +4 more
core   +1 more source

Hyperosmotic stress induces PARP1‐mediated HPF1‐dependent mono(ADP‐ribosyl)ation

FEBS Letters, EarlyView.
Sorbitol‐induced hyperosmotic stress rapidly induces reversible mono(ADP‐ribosyl)ation (MARylation) on PARP1 without the signs of genotoxic signaling. We show that PARP1 autoMARylation is HPF1 dependent and forms hydroxylamine‐resistant O‐glycosidic linkages.
Anna Georgina Kopasz, Mihály Mérey, Rebeka Vásárhelyi, Ramóna Pék, Victor Imburchia, László Henn, Adrián Kószó, Nicholas D. Lakin, Ivan Ahel, Sébastien Huet, Ágnes Czibula, Gyula Timinszky   +11 more
wiley   +1 more source

Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models

Biomimetics
Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning.
Yinglong Dang, Xiaoguang Gao, Zidong Wang   +2 more
doaj   +1 more source