Results 171 to 180 of about 155,735 (298)
Boosting Classifiers for Drifting Concepts [PDF]
This paper proposes a boosting-like method to train a classifier ensemble from data streams. It naturally adapts to concept drift and allows to quantify the drift in terms of its base learners.
Klinkenberg, Ralf, Scholz, Martin
core
AI‐Designed Cyclic Peptides Enable Controllable Modulation of the CD28 Immune Checkpoint
AI‐designed cyclic peptides enable controllable modulation of the CD28 immune checkpoint through reversible disruption of CD28‐CD80/CD86 interactions. The lead peptide, CIP‐3, suppresses T‐cell activation without intrinsic agonist activity, demonstrates dose‐dependent efficacy in a murine colitis model, and attenuates inflammatory cytokine production ...
Katarzyna Kuncewicz +4 more
wiley +1 more source
This work proposes and constructs the Hefei‐NAMD‐S framework based on machine learning stacked models to investigate the relationship between local polarization and non‐radiative recombination. The results indicate that, compared with A‐site local polarization, B‐site local polarization shows a more evident association with the non‐radiative ...
Bing Yang +13 more
wiley +1 more source
PDIA6–SCD1 Axis Rewires Lipid Metabolism to Drive Gastric Cancer Progression
Protein disulfide isomerase A6 (PDIA6) is identified as an oncogenic driver in gastric cancer. PDIA6 directly binds and stabilizes SCD1 by limiting its ubiquitin–proteasome‐mediated degradation, thereby sustaining monounsaturated fatty acid (MUFA)‐enriched lipid homeostasis and lipid metabolic reprogramming.
Zhen Tian +13 more
wiley +1 more source
Software dominates modern enterprises, affecting numerous functions. Software firms constantly experiment with new methodologies to define and assess software quality to stay competitive and ensure excellence.
Jameel Saraireh +2 more
doaj +1 more source
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu +5 more
wiley +1 more source
Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng +7 more
wiley +1 more source
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
This work introduces state‐convergent polymerization (SCP), a polymerization framework in which chemically diverse reaction pathways converge toward a reproducible functional polymeric state rather than a defined molecular structure. Using melanin and polydopamine as exemplars, SCP explains how robust polymer functions emerge under chemical and ...
Seonki Hong
wiley +1 more source
AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling
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 +4 more
wiley +1 more source

