Results 171 to 180 of about 7,255,480 (346)

Graphical Reasoning with Bayesian Networks

, 2007
Nowadays, Bayesian networks are seen by many researchers as standard tools for reasoning with uncertainty. Despite the fact that Bayesian networks are graphical representations, representing dependence and independence information, normally the emphasis of the visualisation of the reasoning process is on showing changes in the associated marginal ...
Flesch, I., Lucas, P.J.F.
openaire   +4 more sources

Lessons From Drug Discovery for Cryoprotective Agent Design: An AI‐Oriented Perspective

Advanced Science, EarlyView.
Cryoprotectant design is reframed through the lens of drug discovery as a multiparameter optimization problem. This perspective highlights how AI and systematic design strategies could enable safer, more effective cryoprotectants, while identifying key limitations that currently constrain predictive progress in cryobiology. ABSTRACT Cryopreservation is
Dominika Wilczok, Jesús Valdés‐Hernández, Varinia Bernales, Alán Aspuru‐Guzik, Alex Zhavoronkov   +4 more
wiley   +1 more source

Fourier Bayesian networks: A novel approach for network structure inference with application to brain connectivity studies from magnetoencephalographic recordings [PDF]

, 2012
This thesis proposes a novel approach for connectivity studies in Electrophysiology and Neuroimaging based on Bayesian Network (BN) analysis in the Fourier domain that is named Fourier Bayesian Networks (FBNs). FBNs use the complex information available
Peraza Rodriguez, Luis Ramon
core  

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source

Conformational Snapshots of CydDC in a Native Lipid Bilayer Coupling Heme Transport to Antibiotic Resistance

Advanced Science, EarlyView.
Phylogenetic and biochemical analyses of the heme transporter CydDC reveal its functional conservation throughout bacterial evolution and demonstrate its unique asymmetric allosteric mechanism. Furthermore, impairment of CydDC function directly affects bacterial antibiotic resistance and likely compromises antibiotic efficacy through drug efflux.
Lili Yang, Changbin Zhang, Mengyuan Lyu, Yongbo Luo, Jierou Zhang, Yujiao Chen, Lintao Luo, Wen Qiao, Xiangyangpeng Li, Yu Zhou, Zhongling Wei, Yuling Xiao, Qian Niu, Juan Zhou, Guanglin He, Binwu Ying, Zhaoming Su, Hao Chen, Xiaodi Tang, Haohao Dong   +19 more
wiley   +1 more source

Using Bayesian Networks to Analyze Expression Data

Annual International Conference on Research in Computational Molecular Biology, 2000
N. Friedman, M. Linial, I. Nachman, D. Pe’er   +3 more
semanticscholar   +1 more source

T2T Genome Assembly and Multi‐Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte)

Advanced Science, EarlyView.
A gap‐free genome assembly and multi‐omics comparison of the terrestrial slug Laevichaulis alte with an aquatic relative reveal that expansion of the VEGF family orchestrates mucus production, lipid metabolism, and immune defense—highlighting key molecular innovations for conquering life on land.
Gang Wang, Shaofang He, Zhongkai Wang, Aobo Pang, Xiaoli Sun, Rongchen Liu, Fang Wang, Sisi Chen, Zhijuan Bian, Dongcheng Wei, Liuhan Wu, Siyao Zhao, Qiuting Ji, Yiqi Sun, Niying Sun, Yushinta Fujaya, Boping Tang, Kianann Tan, Daizhen Zhang, Lianfu Chen   +19 more
wiley   +1 more source

Inductive transfer for learning Bayesian networks [PDF]

, 2009
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with different conditions; or in industrial diagnosis, where there is ...
LUIS ENRIQUE SUCAR SUCCAR, EDUARDO FRANCISCO MORALES MANZANARES   +1 more
core  

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

, 2015
A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply.
Brookes, Justin D., Ingrid Chorus, Boqiang Qin, Chorus, I., Watkinson, Andrew J, Justin D. Brookes, Hamilton, David P, James A. Rusak, Rusak, James A, Sparber, K., Rigosi, A., Hipsey, M., Matthew Hipsey, Brookes, J., Bois, J., Hipsey, Matthew, Bomchul Kim, Hanson, P., Brookes, Justin D, Hanson, Paul, Hipsey, Matthew R., Qin, Boqiang, Kim, Bomchul, Karin Sparber, Hanson, Paul C., Andrew J. Watkinson, Hamilton, D., Sparber, Karin, Bois, Julie, Rigosi, Anna, Watkinson, Andrew J., Julie Bois, Rusak, J., Anna Rigosi, Paul Hanson, David P. Hamilton, Rusak, James A., Chorus, Ingrid, Watkinson, A., Kim, B., Qin, B., Hamilton, David P.   +41 more
core   +1 more source

Gated Bayesian Networks.

, 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