Results 101 to 110 of about 155,742 (245)

Multimodal AI‐Driven Identification of Dehydrocostus Lactone as a Potent Renal Fibrosis Attenuator Targeting IQGAP1

Advanced Science, EarlyView.
Renal fibrosis, a hallmark of CKD, lacks effective treatments. Herein, we developed a multimodal AI model (TCM‐SPred) to identify anti‐fibrotic agents and found that dehydrocostus lactone (DCL) targets IQGAP1 to inhibit Wnt signaling, blocking the interaction between IQGAP1 and CCT3, demonstrating potent anti‐fibrotic activity in vitro and in vivo ...
Weijiang Lin, Wenzhuo Xu, Kang Liu, Ping Wang, Zhenzhen Zhu, Wenyu Lu, Zhe Zheng, Xiaoqian Peng, Xunkai Yin, Shulan Mei, An Pan, Jian Liu, Lihong Hu   +12 more
wiley   +1 more source

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

Advanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang, Yang Wu, Feng Zhang, Parthiban Periasamy, Haiyue You, Denise Goh, Rachel Elizabeth Ann Fincham, Xin Ning, Danping Wu, Lu Liu, Ying Jiang, Zhiwen Qian, Joe Yeong, Yan Zhang   +13 more
wiley   +1 more source

Spatial Scene Memories Are Biased Towards a Fixed Amount of Semantic Information. [PDF]

Open Mind (Camb), 2023
Greene MR, Trivedi D.
europepmc   +1 more source

Information-theoretic limits on compression of semantic information

China Communications
As conventional communication systems based on classic information theory have closely approached the limits of Shannon channel capacity, semantic communication has been recognized as a key enabling technology for the further improvement of communication performance.
Tang, Jiancheng, Yang, Qianqian, Zhang, Zhaoyang   +2 more
openaire   +2 more sources

Machine Learning‐Guided Engineering of Protein Phase Separation Properties in Immune Regulation

Advanced Science, EarlyView.
PScalpel, a machine learning model integrating protein structure extraction, graph contrastive learning, and a genetic algorithm, guides the engineering of protein phase separation ability. It adopts transfer learning methods to provide predictive recommendations for protein phase separation ability changes through single amino acid mutations in a ...
Chenqiu Zhang, Jia Wang, Zhe Wang, Liyan Zhu, Sihui Cai, Luzhi Zhan, Haorui Liang, Yaoxing Wu, Jianqiang Li, Jun Cui   +9 more
wiley   +1 more source

FGSI: distant supervision for relation extraction method based on fine-grained semantic information. [PDF]

Sci Rep, 2023
Sun C, Ji W, Zhou G, Guo H, Yin Z, Yue Y.   +5 more
europepmc   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

A Novel Strategy for Extracting Richer Semantic Information Based on Fault Detection in Power Transmission Lines. [PDF]

Entropy (Basel), 2023
Yan S, Li J, Wang J, Liu G, Ai A, Liu R.
europepmc   +1 more source

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

Advanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen, Jingrui Zhong, Xiaochun Zhang, Jingke Chen, Lin Guo, Xiaoliang Xiong, Xiaonan Zhang, Xiangyu Liu, Bailong Xiao, Boxue Tian   +9 more
wiley   +1 more source