We are analyzing https://link.springer.com/article/10.1007/s11432-024-4098-3.

Title:
BioKG-CMI: a multi-source feature fusion model based on biological knowledge graph for predicting circRNA-miRNA interactions | Science China Information Sciences
Description:
This study proposes a model named BioKG-CMI to predict CMIs based on a biological knowledge graph. Faced with limited data, we employ subcellular localization to generate negative samples that align more closely with biological logic. To mine semantic information in circRNA and miRNA sequences, we introduce the pre-trained model BERT to learn sequence feature representation. Guided by the hypothesis that adjacent molecules have similar functions, we calculate spatial proximity between nodes of the same class. The DisMult algorithm is applied to extract the potential logical rules of the knowledge graph and learn entity and relationship representations. Subsequently, the integration of multi-feature successfully addresses the challenge of expressing the complex biological knowledge graph and overcoming the limitation of single-feature inadequacy. Multiple comparative experiments and case studies demonstrate the robustness of the proposed model.
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Keywords {🔍}

information, article, china, science, wang, biological, graph, model, knowledge, wei, privacy, cookies, content, data, feature, google, scholar, school, university, publish, search, biokgcmi, based, lei, access, grant, log, journal, research, sciences, multisource, fusion, predicting, circrnamirna, interactions, published, zhengwei, zhuhong, discover, nature, sci, download, natural, foundation, author, authors, computer, technology, engineering, supporting,

Topics {✒️}

model named biokg-cmi predicting circrna-mirna interactions multi-feature successfully addresses month download article/chapter pre-trained model bert pdf biokg-cmi privacy choices/manage cookies predict cmis based single-feature inadequacy natural science foundation national science fund 1007/s11432-024-4098-3 access biological knowledge graph full article pdf latent feature analysis biokg-cmi mine semantic information graph neural nets european economic area employ subcellular localization generate negative samples calculate spatial proximity potential logical rules multiple comparative experiments case studies demonstrate random subsequence forests distinguished young scholars xinjiang technical institute figures c1–c5 tables c1–c8 supplementary file 11432_2024_4098_moesm1_esm conditions privacy policy learning conjoint attentions northwestern polytechnical university accepting optional cookies bowei zhao xiaorui su zhengwei li main content log information science journal finder publish article wei supporting information proposed model affiliations school yang li mirna sequences biological logic lei wang china university

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