Results 61 to 70 of about 472,976 (271)
Bivariate Causal Discovery and Its Applications to Gene Expression and Imaging Data Analysis
Frontiers in Genetics, 2018 The mainstream of research in genetics, epigenetics, and imaging data analysis focuses on statistical association or exploring statistical dependence between variables.
Rong Jiao +6 more
doaj +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
Contexts of Causal Discovery [PDF]
Se distinguen dos acepciones del término “contexto de descubrimiento”: La acepción tradicional, que lo contrasta con el contexto de la justificación, y otra, más reciente, que lo relaciona con la metodología de inferencia causal.
Suárez, Mauricio
core +2 more sources
By dawn or dusk—how circadian timing rewrites bacterial infection outcomes
FEBS Letters, EarlyView.The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo +2 more
wiley +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
Causal Discovery in Manufacturing: A Structured Literature Review
Journal of Manufacturing and Materials Processing, 2022 Industry 4.0 radically alters manufacturing organization and management, fostering collection and analysis of increasing amounts of data. Advanced data analytics, such as machine learning (ML), are essential for implementing Industry 4.0 and obtaining ...
Matej Vuković, Stefan Thalmann
doaj +1 more source
Multi-Dimensional Causal Discovery [PDF]
, 2013 We propose a method for learning causal relations within high-dimensional tensor data as they are typically recorded in non-experimental databases. The method allows the simultaneous inclusion of numerous dimensions within the data analysis such as ...
Kostas Stathis +3 more
core +1 more source
Review of Causal Discovery Methods Based on Graphical Models
Frontiers in Genetics, 2019 A fundamental task in various disciplines of science, including biology, is to find underlying causal relations and make use of them. Causal relations can be seen if interventions are properly applied; however, in many cases they are difficult or even ...
Clark Glymour, Kun Zhang, Peter Spirtes
doaj +1 more source
Distinguishing cause from effect using observational data: methods and benchmarks [PDF]
, 2015 The discovery of causal relationships from purely observational data is a fundamental problem in science. The most elementary form of such a causal discovery problem is to decide whether X causes Y or, alternatively, Y causes X, given joint observations ...
Janzing, Dominik +4 more
core +1 more source
The role and implications of mammalian cellular circadian entrainment
FEBS Letters, EarlyView.At their most fundamental level, mammalian circadian rhythms occur inside every individual cell. To tell the correct time, cells must align (or ‘entrain’) their circadian rhythm to the external environment. In this review, we highlight how cells entrain to the major circadian cues of light, feeding and temperature, and the implications this has for our
Priya Crosby
wiley +1 more source