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Msaidizi

Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Uchambuzi wa Kifilojenetiki wa Mfululizo wa Muda×Uchambuzi wa Utekelezaji Tofauti wa RNA-seq×
NyanjaBioinformatikiBioinformatiki
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili2000s (molecular clock methods earlier; BEAST framework 2007)2008–2010 (RNA-seq DE methodology established)
MwanzilishiAlexei J. Drummond, Andrew Rambaut, and colleaguesMultiple groups; foundational methods from Anders & Huber (DESeq, 2010), Robinson, McCarthy & Smyth (edgeR, 2010)
AinaEvolutionary bioinformatics pipelineQuantitative genomics pipeline
Chanzo asiliaDrummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7, 214. DOI ↗Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550. DOI ↗
Majina mbadalatemporal phylogenetics, time-resolved phylogenetics, molecular clock phylogenetics, phylodynamicsRNA-seq DE analysis, transcriptomic differential expression, bulk RNA-seq DE, DEA
Zinazohusiana66
MuhtasariTime-series phylogenetic analysis reconstructs the evolutionary history of organisms or genetic variants using sequences sampled at known time points. By incorporating sampling dates directly into the model, it estimates divergence times, substitution rates, and ancestral relationships on an absolute timescale — making it essential for studying viral outbreaks, ancient DNA dynamics, and rapid microbial evolution.RNA-seq differential expression (DE) analysis identifies genes whose transcript abundance differs significantly between two or more biological conditions — for example, treated versus control, or diseased versus healthy tissue. Starting from raw sequencing reads, the pipeline moves through alignment, count-based normalization, statistical modeling of count dispersion, hypothesis testing, and multiple-testing correction to produce a ranked list of differentially expressed genes accompanied by fold-change estimates and adjusted p-values.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

Nenda kwenye utafutaji Pakua slaidi

ScholarGateLinganisha mbinu: Time-series phylogenetic analysis · RNA-seq Differential Expression. Imepatikana 2026-06-19 kutoka https://scholargate.app/sw/compare