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gene_networks_inference [2019/08/16 03:09]
admin [Data]
gene_networks_inference [2019/09/04 06:56] (current)
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   - Guillamot, Maria, Luisa Cimmino, and Iannis Aifantis. "The impact of DNA methylation in hematopoietic malignancies."​ [[http://​www.cell.com/​trends/​cancer/​pdf/​S2405-8033(15)00089-8.pdf|Trends in cancer]] 2.2 (2016): 70-83. \\  Reviews and references DNA methylation studies and datasets on AML. E.g., [[http://​www.sciencedirect.com/​science/​article/​pii/​S1535610809004206|Figueroa]] et al. used DNA methylation for classification of 344 AML cases. [[http://​journals.plos.org/​plosgenetics/​article?​id=10.1371/​journal.pgen.1002781|Akalin]] et al. related DNA methylation patterns with mutations in 5 AML cases. "The methylation status of specific genes can predict the future survival of AML patients, suggesting that DNA methylation is a biomarker for clinical outcome"​ see e.g., Figueroa et al, [[http://​www.bloodjournal.org/​content/​bloodjournal/​113/​6/​1315.full.pdf?​sso-checked=true|Jiang]] 2009 (studied MDS to AML progression in 184 cases), and [[http://​www.bloodjournal.org/​content/​115/​3/​636.long?​sso-checked=true|Bullinger]] 2010 (analyzed 92 genomic regions in 182 patients).   - Guillamot, Maria, Luisa Cimmino, and Iannis Aifantis. "The impact of DNA methylation in hematopoietic malignancies."​ [[http://​www.cell.com/​trends/​cancer/​pdf/​S2405-8033(15)00089-8.pdf|Trends in cancer]] 2.2 (2016): 70-83. \\  Reviews and references DNA methylation studies and datasets on AML. E.g., [[http://​www.sciencedirect.com/​science/​article/​pii/​S1535610809004206|Figueroa]] et al. used DNA methylation for classification of 344 AML cases. [[http://​journals.plos.org/​plosgenetics/​article?​id=10.1371/​journal.pgen.1002781|Akalin]] et al. related DNA methylation patterns with mutations in 5 AML cases. "The methylation status of specific genes can predict the future survival of AML patients, suggesting that DNA methylation is a biomarker for clinical outcome"​ see e.g., Figueroa et al, [[http://​www.bloodjournal.org/​content/​bloodjournal/​113/​6/​1315.full.pdf?​sso-checked=true|Jiang]] 2009 (studied MDS to AML progression in 184 cases), and [[http://​www.bloodjournal.org/​content/​115/​3/​636.long?​sso-checked=true|Bullinger]] 2010 (analyzed 92 genomic regions in 182 patients).
   - John [[https://​www.youtube.com/​watch?​v=Vyhq7GZFnes|Quackenbush'​s]] talk entitled: "Using Networks to Understand the Genotype-Phenotype Connection"​.   - John [[https://​www.youtube.com/​watch?​v=Vyhq7GZFnes|Quackenbush'​s]] talk entitled: "Using Networks to Understand the Genotype-Phenotype Connection"​.
-  - Saelens, Wouter, Robrecht Cannoodt, and Yvan Saeys. "A comprehensive evaluation of module detection methods for gene expression data." [[https://​www.nature.com/​articles/​s41467-018-03424-4|Nature communications]] 9.1 (2018): 1090.  \\  "​Graph-based,​ representative-based,​ and hierarchical clustering all performed equally well, with the clustering method FLAME (Fuzzy clustering by Local Approximation of Memberships),​ one of the only clustering methods able to detect overlap, slightly outperforming other clustering methods"​ including WGCNA. Regularity networks that had been inferred using other data, e.g., "​binding motifs in active enhancers",​ were used as gold standard.+  - Saelens, Wouter, Robrecht Cannoodt, and Yvan Saeys. "A comprehensive evaluation of module detection methods for gene expression data." [[https://​www.nature.com/​articles/​s41467-018-03424-4|Nature communications]] 9.1 (2018): 1090. \\  "​Graph-based,​ representative-based,​ and hierarchical clustering all performed equally well, with the clustering method FLAME (Fuzzy clustering by Local Approximation of Memberships),​ one of the only clustering methods able to detect overlap, slightly outperforming other clustering methods"​ including WGCNA. Regularity networks that had been inferred using other data, e.g., "​binding motifs in active enhancers",​ were used as gold standard. 
 +  - Choobdar, Sarvenaz, et al. "​Assessment of network module identification across complex diseases."​ [[https://​www.nature.com/​articles/​s41592-019-0509-5|Nature Methods]] 16.9 (2019): 843-852. \\  "The popular weighted gene co-expression network analysis (WGCNA) method7 did not perform competitively."​