Results 261 to 270 of about 19,982 (307)

CLinNET: An Interpretable and Uncertainty‐Aware Deep Learning Framework for Multi‐Modal Clinical Genomics

Advanced Science, EarlyView.
Identifying disease‐causing genes in neurocognitive disorders remains challenging due to variants of uncertain significance. CLinNET employs dual‐branch neural networks integrating Reactome pathways and Gene Ontology terms to provide pathway‐level interpretability of genomic alterations.
Ivan Bakhshayeshi, Mohammad Mahdi Hosseini, Ahmadreza Argha, Roxana Zahedi, Nigel H. Lovell, Hamid Alinejad‐Rokny   +5 more
wiley   +1 more source

Accurate prediction of substitution rates at protein sites with a mutation-selection model. [PDF]

Sci Rep
André I.
europepmc   +1 more source

QSTH 0.A – Entropic Spatial Dimension: Empirical Alignments and External Correlations (Component)

Rostislav Stepanik
openalex   +1 more source

Learned Conformational Space and Pharmacophore Into Molecular Foundational Model

Advanced Science, EarlyView.
The Ouroboros model introduces two orthogonal modules within a unified framework that independently learn molecular representations and generate chemical structures. This design enables flexible optimization strategies for each module and faithful structure reconstruction without prompts or noise.
Lin Wang, Yifan Wu, Hao Luo, Minglong Liang, Yihang Zhou, Cheng Chen, Chris Liu, Jun Zhang, Yang Zhang   +8 more
wiley   +1 more source

Pre-Warning for the Remaining Time to Alarm Based on Variation Rates and Mixture Entropies. [PDF]

Entropy (Basel)
Yang Z, Wang J, Li H, Gao S.
europepmc   +1 more source

An empirical study of maximum entropy approach for part-of-speech tagging of Vietnamese texts

, 2010
Phuong Le-Hong, Azim Roussanaly, Thị Minh Huyền Nguyễn, Mathias Rossignol   +3 more
openalex   +1 more source

A Quantum Framework for Protein Binding‐Site Structure Prediction on Utility‐Level Quantum Processors

Advanced Science, EarlyView.
This study presents a hybrid quantum‐classical framework for accurate prediction of protein structures on utility‐level quantum processors. We evaluate the practical application of the Variational Quantum Eigen‐solver (VQE) in protein structure prediction and demonstrate its superiority over state‐of‐the‐art deep learning methods in molecular docking ...
Yuqi Zhang, Yuxin Yang, William Martin, Kingsten Lin, Zixu Wang, Cheng‐Chang Lu, Weiwen Jiang, Ruth Nussinov, Joseph Loscalzo, Qiang Guan, Feixiong Cheng   +10 more
wiley   +1 more source

Unravelling the thermodynamic properties of soil ecosystems in mature beech forests. [PDF]

Sci Rep
Barros N, Popovic M, Molina-Valero J, Lestido-Cardama Y, Pérez-Cruzado C.   +4 more
europepmc   +1 more source

A Machine Learning‐Driven Pore‐Scale Network Model Coupling Reaction Kinetics and Interparticle Transport for Catalytic Process Design

Advanced Science, EarlyView.
Designing catalytic processes in porous reactors requires resolving coupled multiscale reaction–transport phenomena. We develop a machine‐learning‐accelerated pore‐scale dual‐network model with kinetics (DNMK), which captures reaction kinetics, pore‐scale transport, and reactor‐level behavior.
Ming‐Liang Qu, Zhao‐Bin Ding, Dingyue Zhang, Sajjad Foroughi, Huanhao Chen, Zi‐Tao Yu, Jiyizhe Zhang, Lifeng Xiao, Martin J. Blunt, Xiaolei Fan, Qingyang Lin   +10 more
wiley   +1 more source

Exploring topological indices and entropy measure via rational curve fitting models for calcium hydroxide network. [PDF]

Sci Rep
Huang R, Hanif MF, Siddiqui MK, Hanif MF, Hussain M, Petros FB.   +5 more
europepmc   +1 more source