The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Network‐based global inference of human disease genes
Open accessAbstract
Deciphering the genetic basis of human diseases is an important goal of biomedical research. On the basis of the assumption that phenotypically similar diseases are caused by functionally related genes, we propose a computational framework that integrates human protein-protein interactions, disease phenotype similarities, and known gene-phenotype associations to capture the complex relationships between phenotypes and genotypes. We develop a tool named CIPHER to predict and prioritize disease genes, and we show that the global concordance between the human protein network and the phenotype network reliably predicts disease genes. Our method is applicable to genetically uncharacterized phenotypes, effective in the genome-wide scan of disease genes, and also extendable to explore gene cooperativity in complex diseases. The predicted genetic landscape of over 1000 human phenotypes, which reveals the global modular organization of phenotype-genotype relationships. The genome-wide prioritization of candidate genes for over 5000 human phenotypes, including those with under-characterized disease loci or even those lacking known association, is publicly released to facilitate future discovery of disease genes.
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DAVID: Database for Annotation, Visualization, and Integrated Discovery
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Probing genetic overlap among complex human phenotypes
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Network medicine: a network-based approach to human disease
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ToppGene Suite for gene list enrichment analysis and candidate gene prioritization
Chen, J., Bardes, E. E., Aronow, B. J., & Jegga, A. G. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp427 · Cited by 2,952
Interactome Networks and Human Disease
Vidal, M., Cusick, M. E., & Barabási, A.-L. (2011) · Cell · doi:10.1016/j.cell.2011.02.016 · Cited by 1,771
Zhao, L., Zhang, H., Li, N., Chen, J., Xu, H., Wang, Y., & Liang, Q. (2023) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2023.116306 · Cited by 963
Structure and dynamics of molecular networks: A novel paradigm of drug discovery
Csermely, P., Korcsmáros, T., Kiss, H. J. M., London, G., & Nussinov, R. (2013) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2013.01.016 · Cited by 892
Metadata
- Authors
- Wu, X., Jiang, R., Zhang, M. Q., & Li, S.
- Venue
- Molecular Systems Biology
- Published
- 2008-01
- Volume
- 4
- Issue
- 1
- Pages
- 189-189
- ISSN
- 1744-4292 (ISSN-L)
- OpenAlex
- W2097498614
- Cited by
- 660
- References
- 12
- FWCI
- 17.74
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
