Dataset Information

DIA-SIFT: A precursor and product ion filter for accurate stable isotope data-independent acquisition proteomics

ABSTRACT: Human 293T cells grown in SILAC media, mixed at known ratios (1/5, 1/3, 1/2, 1, 2, 3, 5). Data acquired using the UDMSE method on a Synapt G2-S. Accompanies the DIA-SIFT project (github.com/martin-lab/DIA-SIFT).

INSTRUMENT(S): Synapt MS

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Sarah Haynes

LAB HEAD: Brent Martin

PROVIDER: PXD009949 | Pride | 2018-07-16

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	293T_SILAC_1to1_rep01.raw.zip	Raw
	293T_SILAC_1to1_rep01_IA_final_fragment.csv	Csv
	293T_SILAC_1to1_rep01_IA_final_peptide.csv	Csv
	293T_SILAC_1to1_rep01_IA_final_protein.csv	Csv
	293T_SILAC_1to1_rep02.raw.zip	Raw

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Publications

DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics.

Haynes Sarah E SE Majmudar Jaimeen D JD Martin Brent R BR

Analytical chemistry 20180719 15

Quantitative mass spectrometry-based protein profiling is widely used to measure protein levels across different treatments or disease states, yet current mass spectrometry acquisition methods present distinct limitations. While data-independent acquisition (DIA) bypasses the stochastic nature of data-dependent acquisition (DDA), fragment spectra derived from DIA are often complex and challenging to deconvolve. In-line ion mobility separation (IMS) adds an additional dimension to increase peak c ...[more]

PMID: 29989796

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