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تحلیل پروتئومیکس سری‌های زمانی×تحلیل بیان افتراقی RNA-seq×
حوزهزیست‌اطلاعاتیزیست‌اطلاعاتی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش2000s (quantitative framework: Gygi et al. 1999; time-series designs: 2004–2010)2008–2010 (RNA-seq DE methodology established)
پدیدآورMultiple groups; Gygi et al. (1999) established quantitative proteomics; time-series designs emerged in the 2000s with LC-MS/MS workflowsMultiple groups; foundational methods from Anders & Huber (DESeq, 2010), Robinson, McCarthy & Smyth (edgeR, 2010)
نوعQuantitative longitudinal omics pipelineQuantitative genomics pipeline
منبع بنیادینLemeer, S., & Heck, A. J. R. (2012). The phosphoproteomics data explosion. Current Opinion in Chemical Biology, 16(1–2), 1–8. link ↗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 ↗
نام‌های دیگرlongitudinal proteomics, temporal proteomics, dynamic proteomics, time-course proteomicsRNA-seq DE analysis, transcriptomic differential expression, bulk RNA-seq DE, DEA
مرتبط66
خلاصهTime-series proteomics analysis quantifies protein abundance across two or more ordered time points to reveal how the proteome changes dynamically in response to stimuli, developmental stages, or disease progression. By combining mass spectrometry-based protein quantification with statistical models designed for temporal data, the method identifies proteins with significant expression trends, oscillatory patterns, or delayed responses that cannot be detected in single time-point studies.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.
ScholarGateمجموعه‌داده
  1. v1
  2. 2 منابع
  3. PUBLISHED
  1. v1
  2. 2 منابع
  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Time-series proteomics analysis · RNA-seq Differential Expression. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare