Results 101 to 110 of about 2,534 (254)

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
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, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

A Foundation Model Based CT Biomarker for Non‐Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non‐Small Cell Lung Cancer

Advanced Science, EarlyView.
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu, Shuchang Zhou, Qin Peng, Xiao Bao, Xiaodan Ye, Ahmet Görkem Er, Tong Tong, Mirabela Rusu, Yajia Gu, Mailin Chen, Jing Gong   +10 more
wiley   +1 more source

Signalling Entropy Across Measurement Scales: A Compositional Dilution Lemma and Cross-Modality Invariance for Information-Theoretic Analysis of Cancer Transcriptomes

Entropy
We develop a unified information-theoretic framework for the analysis of cancer transcriptomic dysregulation across measurement modalities. Three functionals capture distributional, network-aware, and joint-dependence aspects of expression: the Shannon ...
Ömer Akgüller, Mehmet Ali Balcı, Ceren Uçmakoğlu, Lucian Gaban   +3 more
doaj   +1 more source

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

Advanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li, Jialuo Xu, Gaoyuan Du, Xiangting Jia, Dongmin Zhao, Chunyan Zhou, Kexin Xiao, Jia Gu, Junnan Zhu, Xuequn Shang   +9 more
wiley   +1 more source

From Visual Attributes to Adjectives through Decompositional Distributional Semantics

Transactions of the Association for Computational Linguistics, 2021
Angeliki Lazaridou, Georgiana Dinu, Adam Liska, Marco Baroni   +3 more
doaj   +1 more source

Exploratory Topic Modeling with Distributional Semantics [PDF]

, 2015
As we continue to collect and store textual data in a multitude of domains, we are regularly confronted with material whose largely unknown thematic structure we want to uncover. With unsupervised, exploratory analysis, no prior knowledge about the content is required and highly open-ended tasks can be supported.
openaire   +2 more sources

Mining HPV Vaccine Knowledge Structures of Young Adults From Reddit Using Distributional Semantics and Pathfinder Networks. [PDF]

Cancer Control, 2020
Amith M, Cohen T, Cunningham R, Savas LS, Smith N, Cuccaro P, Gabay E, Boom J, Schvaneveldt R, Tao C.   +9 more
europepmc   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

Advanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu, Fumiaki Iwane, Minsu Zhang, Leonardo G. Cohen, José del R. Millán   +4 more
wiley   +1 more source