Results 131 to 140 of about 68,890 (299)
Advanced Intelligent Discovery, EarlyView.This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source
Onk-Dimensional Balanced Binary Trees
, 1996 An amortized analysis of the insertion and deletion algorithms ofk-dimensional balanced binary trees (kBB-trees) is performed. It is shown that the total rebalancing time for a mixed sequence ofminsertions and deletions in akBB-tree of sizenisO(k(m+n ...
Vijay K. Vaishnavi, Vaishnavi, Vijay K.
core +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Iterative Formulas for Enumerating Binary Trees
, 1997 Enumeration is an important aspect for combinatorial properties of binary trees. Traditional solutions for enumerating binary trees are expressed by algorithms and most of them are recursive. In this paper, we give our solutions by iterative formulas for
牛島, 和夫 +2 more
core
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
2-Binary trees: Bijections and related issues
, 2008 A 2-binary tree is a binary rooted tree whose root is colored black and the other vertices are either black or white. We present several bijections concerning different types of 2-binary trees as well as other combinatorial structures such as ternary ...
Gu, Nancy S.S. +2 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
Optimal Binary Split Trees Revisited
, 1994 Binary split trees were designed for static data sets and algorithms to construct optimal binary split trees have received some attention in the literature.
David A. Spuler, D. A. Spuler
core
Advanced Intelligent Discovery, EarlyView.We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi +3 more
wiley +1 more source