Results 281 to 290 of about 540,625 (369)

Investigation on dynamical perspective of soliton solutions to the nonlinear integrable Akbota equation through a generalized analytical technique. [PDF]

Sci Rep
Iqbal M, Faridi WA, Alrashdi HD, Algethamie R, Aljohani A, El-Meligy M, Nazar NM, Alnowibet KA.   +7 more
europepmc   +1 more source

Mathematical theory of thermodynamics of computation

, 1992
Ming Li, Paul Vitányi
openalex   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

A geometric graph-based deep learning model for drug-target affinity prediction. [PDF]

BMC Bioinformatics
Rana MM, Mukta FT, Nguyen DD.
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Re-weighted estimation of the transition probability density for second-order diffusion processes. [PDF]

PLoS One
Li Y, Wang Y, Tang M.
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Dynamical modeling of TNF-α, IL-6, and IL-10 interactions in stroke-induced inflammation. [PDF]

PLoS One
Arishi FAM, Rambely AS, Abdul Razak F.
europepmc   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Topological modeling and QSPR based prediction of physicochemical properties of bioactive polyphenols. [PDF]

Sci Rep
Hakeem A, Ullah A, Zaman S, Mahmoud EE, Ahmad H, Ali P, Belay MB.   +6 more
europepmc   +1 more source