เปรียบเทียบวิธี

	การวิเคราะห์โปรตีโอมิกส์อนุกรมเวลา	การแสดงออกที่แตกต่างกันของ RNA-seq แบบอนุกรมเวลา
สาขาวิชา	ชีวสารสนเทศศาสตร์	ชีวสารสนเทศศาสตร์
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2000s (quantitative framework: Gygi et al. 1999; time-series designs: 2004–2010)	2006–2018 (principal methods established)
ผู้ริเริ่ม	Multiple groups; Gygi et al. (1999) established quantitative proteomics; time-series designs emerged in the 2000s with LC-MS/MS workflows	Conesa et al. (maSigPro, 2006); extended by Fischer et al. (ImpulseDE2, 2018) and others
ประเภท	Quantitative longitudinal omics pipeline	Computational genomics pipeline
แหล่งต้นตำรับ	Lemeer, S., & Heck, A. J. R. (2012). The phosphoproteomics data explosion. Current Opinion in Chemical Biology, 16(1–2), 1–8.	Conesa, A., Nueda, M. J., Ferrer, A., & Talon, M. (2006). maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics, 22(9), 1096–1102.
ชื่อเรียกอื่น	longitudinal proteomics, temporal proteomics, dynamic proteomics, time-course proteomics	longitudinal RNA-seq DE analysis, temporal transcriptomics, time-course RNA-seq, dynamic DE analysis
ที่เกี่ยวข้อง	6	6
สรุป	Time-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.	Time-series RNA-seq differential expression analysis identifies genes whose expression levels change systematically across ordered time points — such as during development, disease progression, or response to a treatment. Unlike two-condition DE analysis, it explicitly models the temporal structure of the data, capturing dynamic gene expression trajectories rather than a single snapshot contrast. Tools such as maSigPro, ImpulseDE2, and splineTimeR have been developed specifically for this design.