Results 231 to 240 of about 1,282,535 (297)
SA-MTP: a structure-aware framework for multifunctional therapeutic peptide annotation. [PDF]
Yu W, Li Z, Xu W, Zhao Y, Sun N.
europepmc +1 more source
Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen +14 more
wiley +1 more source
Edge-aware GAT-based protein binding sites prediction. [PDF]
Yang W, Zhang H, Qiu W, Xiao X, Lin W.
europepmc +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source
Research Progress of Sepsis and Nutrition: A Bibliometric and Visualized Analysis. [PDF]
Shang L +9 more
europepmc +1 more source
Near‐surface deuterium enrichment profiles for different microstructural types of TiAl after exposure at 700 °C in a heavy water‐containing environment. The deuterium levels are significantly higher than expected from natural occurrence, indicating that the heavy water dissociated during the exposure treatment and entered the specimens.
Jonathan D. H. Paul +5 more
wiley +1 more source
Multiplex functional connectome graph transformer for cognitive vulnerability in dialysis-treated chronic kidney disease. [PDF]
Zhai J, Pang J, Lei X, Yan K, Zhou J.
europepmc +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
From trees to graphs: rethinking phylogeny in microbiome prediction. [PDF]
Yu Q, Bai D, Wang Y, Liu Y-X.
europepmc +1 more source

