Results 111 to 120 of about 62,767 (259)
Organizations strive to maximize efficiency in their manufacturing processes, yet they must also consider broader repercussions, as industrial activity directly impacts the environment and society.
Salvador Perez-Garcia +2 more
doaj +1 more source
Mechanism‐Informed Machine Learning Enables Discovery of Oncolytic Peptides for Cancer Immunotherapy
MISPOP integrates ensemble learning with membrane‐active physicochemical priors to identify Dermaseptin‐S9, a natural oncolytic peptide that disrupts tumor membranes, triggers immunogenic cell death, and shows strong antitumor activity. The study illustrates a mechanism‐informed route from peptide sequence data to cancer immunotherapy leads.
Wen Zhang +11 more
wiley +1 more source
This paper describes deep neural network (DNN) models based on hyperparameter optimization for the prediction of the compressive strength of concrete. The novelty of this research lies in the implementation of optimized hyperparameters to train the DNN ...
Mohammed Naved +2 more
doaj +1 more source
A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren +5 more
wiley +1 more source
PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li +10 more
wiley +1 more source
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen +7 more
wiley +1 more source
Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen +3 more
wiley +1 more source
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li +13 more
wiley +1 more source
stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi‐Omics
stMixer is an unsupervised framework for scalable integration and label transfer across spatial histology and multi‐slide multi‐omics data with incomplete modality overlap. It combines self‐looped cross‐attention, multimodal metric learning, and graph‐guided cluster voting to align heterogeneous sections, correct batch effects, and propagate ...
Qixing Yang +3 more
wiley +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

