Results 191 to 200 of about 30,563 (303)

Boosting Sensory Nerve‐to‐Bone Interactions Enhances Hedgehog Mediated Calvarial Bone Repair

Advanced Science, EarlyView.
Boosting sensory nerve activity via TrkA agonism strongly accelerates calvarial bone repair in adult mice. Furthermore, single‐cell RNA sequencing and neuron–bone interactome analyses identify these sensory neurons as a direct neural source of Hedgehog pathway ligands. Consequently, these ligands drive osteoblast differentiation of skeletal progenitors,
Zhao Li, Xin Xing, Beicheng Du, Myles Zhou, Austin Z. Chen, Mary Archer, Chunbao Rao, Manyu Zhu, Masnsen Cherief, Aaron W. James   +9 more
wiley   +1 more source

Revisiting Target‐Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas Sharpshooter

Advanced Science, EarlyView.
TarPass provides a rigorous benchmark for target‐aware de novo molecular generation by jointly evaluating protein‐ligand interactions, molecular plausibility, and drug‐likeness on 18 well‐studied targets. Results show that current models often fail to consistently surpass random baseline in target‐specific enrichment, while post hoc multi‐tier virtual ...
Rui Qin, Zijie Chen, Yurong Li, Meijing Fang, Longji Shen, Yilong Su, Odin Zhang, Qinghan Wang, Qun Su, Jike Wang, Tingjun Hou, Yu Kang   +11 more
wiley   +1 more source

Knowledge graph embedding and alignment of incomplete electronic health records for critical care applications. [PDF]

J Biomed Semantics
Mehryar S, Dumontier M.
europepmc   +1 more source

Towards Characterizing and Quantifying Interpretability of Knowledge Graph Embedding Models

Knowledge graphs are structured representations of real-world information, where entities are connected by edges with labels known as predicates. These graphs contain logical patterns, known as inference patterns, such as symmetry, transitivity and ...
Krishnan, Narayanan Asuri
core  

SpaMode: A Broadly Applicable Framework for Deciphering Spatial Multi‐Omics Using Multimodal Mixture of Disentangled Experts

Advanced Science, EarlyView.
SpaMode introduces a versatile framework for spatial multi‐omics integration across vertical, horizontal, and mosaic scenarios. By disentangling modality‐invariant and variant features through a mixture‐of‐experts mechanism, it adaptively reconfigures spatially heterogeneous signals.
Xubin Zheng, Xinlei Huang, Xiang Zhou, Dian Meng, Ziyue Qiao, Zhiyuan Yuan, Lixin Cheng   +6 more
wiley   +1 more source

Benchmarking knowledge graph embedding models for the prediction of oligogenic combinations. [PDF]

Brief Bioinform
Bosch I, Gravel B, Renaux A, Nowé A, Laan M, Lenaerts T.   +5 more
europepmc   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

Knowledge graph embedding for predicting and analyzing microbial interactions. [PDF]

Sci Rep
Khatbane M, Mangavel C, Borges F, Aridhi S, Toussaint Y.   +4 more
europepmc   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

Advanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen, Jiahui Xie, Yi Liao, Junyu Li, Longqi Liu, Xin Gao, Hongmin Cai   +6 more
wiley   +1 more source

KSMoFinder-knowledge graph embedding of proteins and motifs for predicting kinases of human phosphosites. [PDF]

Bioinform Adv
Anandakrishnan M, Ross KE, Chen C, Vijay-Shanker K, Wu CH.   +4 more
europepmc   +1 more source