Results 261 to 270 of about 7,645,086 (295)

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

Advanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu, Lesong Wei, Jianmin Wang, Yuanpeng Xiong, Ruochi Zhang, Yu Wang, Chao Zha, Qiangcheng Zeng, Xin Gao   +8 more
wiley   +1 more source

SELFormerMM: multimodal molecular representation learning via SELFIES, structure, text, and knowledge graph integration. [PDF]

Bioinformatics
Ulusoy E, Bostancı Ş, Deniz BE, Doğan T.   +3 more
europepmc   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

Advanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia, Siyu Li, Songming Tang, Keju Gu, Shengquan Chen   +4 more
wiley   +1 more source

Dynamic teaching path generation for quadruped robot programming by integrating R-GCN and SBERT. [PDF]

Sci Rep
Wu H.
europepmc   +1 more source

Knowledge graph-enhanced heterogeneous graph neural network for scientific talent innovation potential identification. [PDF]

Sci Rep
Wang R.
europepmc   +1 more source

Advancing passenger next-station prediction via collaborative knowledge graph representational learning. [PDF]

Sci Rep
Duan X, Wang J, Xu Z, Teng W, Tian Y.
europepmc   +1 more source

Cross-residual knowledge graph learning for robust multi-trait gene-trait prioritization in rice. [PDF]

Front Plant Sci
Wang J, Cui X, Fu X, Mao J, Zhang Y, Shan F, Zhou Z, Xing S, Hu X.   +8 more
europepmc   +1 more source

INDIGENA: inductive prediction of disease-gene associations using phenotype ontologies. [PDF]

Bioinformatics
Zhapa-Camacho F, Hoehndorf R.
europepmc   +1 more source

scYeast: a biological-knowledge-guided foundation model on yeast single-cell transcriptomics. [PDF]

Synth Syst Biotechnol
Fan X, Liao W, Xiao L, Yan X, Lu H.
europepmc   +1 more source

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Knowledge graph embedding with concepts

Knowledge-Based Systems, 2019
Abstract Knowledge graph embedding aims to embed the entities and relationships of a knowledge graph in low-dimensional vector spaces, which can be widely applied to many tasks. Existing models for knowledge graph embedding primarily concentrate on entity–relation–entitytriplets, or interact with the text corpus.
Dandan Song, Lejian Liao
exaly   +3 more sources