Results 71 to 80 of about 753,997 (217)

Analysis and Figures from "Causal network inference from gene transcriptional time-series response to glucocorticoids"

, 2020
Jonathan Lu
openalex   +1 more source

Mendelian Randomization Analysis Reveals Causal Relationship Between Obstetric-related Diseases and COVID-19 [PDF]

, 2023
Yan Fang, Dajun Fang
openalex   +1 more source

Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis

Remote Sensing
The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify
Jie Lu, Tianling Qin, Denghua Yan, Xizhi Lv, Zhe Yuan, Jie Wen, Shu Xu, Yuhui Yang, Jianming Feng, Wei Li   +9 more
doaj   +1 more source

Phosphatidylcholine’s influence on Dysmenorrhea: conclusive insights from Mendelian randomization analysis

Frontiers in Genetics
IntroductionThis study aimed to investigate the causal relationship between phosphatidylcholine (PC) levels and dysmenorrhea using Mendelian randomization (MR) analysis.MethodsWe conducted a two-sample MR analysis using GWAS data on PC levels and ...
Yuzheng Li, Shiyao Zhou, Yuchen Huang, Qiuhao Yu, Qibiao Wu, Qibiao Wu, Qibiao Wu, Qibiao Wu   +7 more
doaj   +1 more source

Deep Learning-Enhanced Ocean Acoustic Tomography: A Latent Feature Fusion Framework for Hydrographic Inversion with Source Characteristic Embedding

Information
Ocean Acoustic Tomography (OAT) is an important marine remote sensing technique used for inverting large-scale ocean environmental parameters, but traditional methods face challenges in computational complexity and environmental interference.
Jiawen Zhou, Zikang Chen, Yongxin Zhu, Xiaoying Zheng   +3 more
doaj   +1 more source

Causality-driven localization method for improving ensemble-based Kalman filters in strongly coupled data assimilation system

Frontiers in Marine Science
Strongly coupled data assimilation (SCDA) is a critical tool for improving Earth system predictions by directly integrating observational data into coupled numerical models that simulate interactions among atmospheric, oceanic, and terrestrial components.
Tian'ao Wang, Xuan Wang, Lige Cao, Wei Li, Guijun Han   +4 more
doaj   +1 more source

Nursing Homes to be Paradigms of Path Analysis: A Causal Chain of Structure, Process and Outcome

, 2015
이원주
openalex   +1 more source

Epistemological disputes in the causal link between Zika virus and congenital syndrome: a controversy analysis [PDF]

, 2022
Monique Batista de Oliveira, Marco Akerman   +1 more
openalex   +1 more source

Causal Analysis and Repair of Systems.

, 2022
published
openaire   +2 more sources

Modeling of Interactions between the Zebrafish Hatching Enzyme ZHE1 and A Series of Metal Oxide Nanoparticles: Nano-QSAR and Causal Analysis of Inactivation Mechanisms [PDF]

, 2017
Natalia Sizochenko, Danuta Leszczyńska, Jerzy Leszczyński   +2 more
openalex   +1 more source