Protein structural domain-disease association prediction based on heterogeneous networks

Background Domains can be viewed as portable units of protein structure, folding, function, evolution, and design. Small proteins are often found to be composed of only a single domain, while most large proteins consist of multiple domains for achieving various composite cellular functions. A dysfun...

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Veröffentlicht in:	BMC genomics Jg. 23; H. Suppl 6; S. 869 - 15
Hauptverfasser:	Zhang, Jingpu, Deng, Lianping, Deng, Lei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 10.04.2025 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Algorithms Animal Genetics and Genomics Biomedical and Life Sciences China Commuting Computational Biology - methods Data processing Datasets Disease Disease - genetics Diseases Domain-disease association prediction Genes Health aspects Heterogeneous networks Humans Life Sciences Machine Learning Medical research Medicine, Experimental Meta-path topological feature Microarrays Microbial Genetics and Genomics Physiological aspects Plant Genetics and Genomics Protein Domains Protein folding Protein structure Proteins Proteins - chemistry Proteins - metabolism Proteomics Semantics Structure-function relationships Topology China Domain-disease association prediction Meta-path topological feature Heterogeneous networks
ISSN:	1471-2164, 1471-2164
Online-Zugang:	Volltext
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