Results 121 to 130 of about 328,450 (323)

Accurate Identification of Protein Binding Sites for All Drug Modalities Using ALLSites

Advanced Science, EarlyView.
ALLSites is a unified sequence‐based framework for identifying proteome‐wide binding sites across all drug modalities. It integrates a gated convolutional network with a transformer architecture to capture residue interactions directly from the sequence.
Minjie Mou, Mingkun Lu, Zhimeng Zhou, Yanlin Ren, Xinyuan Yu, Ziqi Pan, Yuan Zhou, Hao Yang, Lingyan Zheng, Shukai Gu, Yang Zhang, Wei Hu, Fengcheng Li, Haibin Dai, Feng Zhu   +14 more
wiley   +1 more source

Context-Dependent Diffusion Network for Visual Relationship Detection

, 2018
Visual relationship detection can bridge the gap between computer vision and natural language for scene understanding of images. Different from pure object recognition tasks, the relation triplets of subject-predicate-object lie on an extreme diversity ...
Kashima Hisashi, Li Chaolong, Liang Kongming, Morris Christopher, Niepert Mathias, Zhuang Bohan   +5 more
core   +1 more source

CACLENS: A Multitask Deep Learning System for Enzyme Discovery

Advanced Science, EarlyView.
CACLENS, a multimodal and multi‐task deep learning framework integrating cross‐attention, contrastive learning, and customized gate control, enables reaction type classification, EC number prediction, and reaction feasibility assessment. CACLENS accelerates functional enzyme discovery and identifies efficient Zearalenone (ZEN)‐degrading enzymes.
Xilong Yi, Yingzhu Tan, Huikang Lin, Guoqing Zhang, Ye Tian, Aibo Wu   +5 more
wiley   +1 more source

Hierarchical micro-blog sentiment classification based on feature fusion

Dianxin kexue, 2016
Sentiment classification is an important issue of opinion mining.It has a high application value to classify sentiment in micro-blogs.As traditional feature selection method has semantic gap,a neural network language model was used to propose a deep ...
Xianying ZHU, Zhen LIU, Wei JIN, Tingting LIU, Cuijuan LIU, Yanjie CHAI   +5 more
doaj   +2 more sources

Prototype-Based Explanation for Semantic Gap Reduction With Distributional Embedding

IEEE Access
The demand for interpretable models has driven the exploration of explainable approaches grounded in human-friendly case-based reasoning. Among these approaches, prototype-based methods have proven effective in performing case-based reasoning by ...
Hyungjun Joo, Sangwoo Hong, Hyeonggeun Han, Youngseok Yoon, Jungwoo Lee   +4 more
doaj   +1 more source

Inferring Gene Regulatory Networks From Single‐Cell RNA Sequencing Data by Dual‐Role Graph Contrastive Learning

Advanced Science, EarlyView.
RegGAIN is a novel and powerful deep learning framework for inferring gene regulatory networks (GRNs) from single‐cell RNA sequencing data. By integrating self‐supervised contrastive learning with dual‐role gene representations, it consistently outperforms existing methods in both accuracy and robustness.
Qiyuan Guan, Jiating Yu, Jieyi Pan, Fan Yuan, Jiadong Ji, Rusong Zhao, Zhi‐Ping Liu, Bingqiang Liu, Ling‐Yun Wu, Duanchen Sun   +9 more
wiley   +1 more source

Virtual machine introspection: towards bridging the semantic gap [PDF]

, 2014
Asit More, Shashikala Tapaswi
openalex   +1 more source

Biomechanics‐Driven 3D Architecture Inference from Histology Using CellSqueeze3D

Advanced Science, EarlyView.
CellSqueeze3D reconstructs 3D cellular architecture from standard 2D histology images using biomechanical constraints and optimization. Validated on clinical datasets, it enables accurate tissue phenotyping, predicts gene mutations, and reveals significant correlations between nuclear‐cytoplasmic ratio entropy and tumor progression.
Yan Kong, Hui Lu
wiley   +1 more source

Semantic Heterogeneity Issues on the Web

, 2012
The Semantic Web is an extension of the traditional Web in which meaning of information is well defined, thus allowing a better interaction between people and computers.
Gracia, Jorge, Mena, Eduardo
core  

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