Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Anàlisi Filogenètica Basada en Xarxes× | Estudi d'associació a escala genòmica (GWAS)× | |
|---|---|---|
| Camp | Bioinformàtica | Bioinformàtica |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 1992–2004 (foundational algorithms); broader development 1990s–2010s | 2005–2007 |
| Autor original≠ | Hans-Jürgen Bandelt & Andreas Dress (split decomposition); David Bryant & Vincent Moulton (Neighbor-Net) | Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007) |
| Tipus≠ | Computational phylogenetic method | Observational genomic association study |
| Font seminal≠ | Bandelt, H.-J., & Dress, A. W. M. (1992). Split decomposition: A new and useful approach to phylogenetic analysis of distance data. Molecular Phylogenetics and Evolution, 1(3), 242–252. link ↗ | Wellcome Trust Case Control Consortium. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678. link ↗ |
| Àlies | phylogenetic network, reticulate phylogenetics, split network analysis, evolutionary network inference | GWAS, genome-wide association analysis, whole-genome association study, WGAS |
| Relacionats | 6 | 6 |
| Resum≠ | Network-based phylogenetic analysis constructs graph-structured representations of evolutionary relationships that explicitly accommodate reticulate events — including hybridization, horizontal gene transfer, recombination, and incomplete lineage sorting — which strictly bifurcating phylogenetic trees cannot represent. Instead of forcing sequences into a single bifurcating tree, the method infers splits or reticulations in the data and visualises them as a network, revealing conflicting phylogenetic signals that are biologically informative. | A genome-wide association study (GWAS) systematically tests hundreds of thousands to millions of single-nucleotide polymorphisms (SNPs) across the human genome for statistical association with a trait or disease. By comparing allele frequencies between cases and controls — or by regressing SNP genotypes on a quantitative phenotype — GWAS identifies genomic loci that harbor common genetic variants contributing to complex traits. Since its large-scale debut in 2007, GWAS has catalogued thousands of robust disease–variant associations across virtually every common human condition. |
| ScholarGateConjunt de dades ↗ |
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