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Stephen A. Martin

Researcher at Applied Biosystems

Publications -  7
Citations -  4750

Stephen A. Martin is an academic researcher from Applied Biosystems. The author has contributed to research in topics: Matrix (chemical analysis) & Blood proteins. The author has an hindex of 6, co-authored 7 publications receiving 4560 citations.

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Journal ArticleDOI

Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents

TL;DR: It is found that inactivation of Upf1p and Xrn1p causes common as well as unique effects on protein expression, and the use of 4-fold multiplexing to enable relative protein measurements simultaneously with determination of absolute levels of a target protein using synthetic isobaric peptide standards.
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Suppression of alpha-cyano-4-hydroxycinnamic acid matrix clusters and reduction of chemical noise in MALDI-TOF mass spectrometry

TL;DR: This sample preparation method resulted in improved spectral quality and was essential for successful database searching for subnanomolar concentrations of protein digests.
Patent

Method for characterizing biomolecules utilizing a result driven strategy

TL;DR: In this article, the authors provided a method for analyzing a sample using a result dependent acquisition strategy, in which the sample is first analyzed by MALDI and MS to produce a first result that is then used to determine a second analysis that is used to analyze the sample again by MS/MS or MSn.
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Identification of Amadori-Modified Plasma Proteins in Type 2 Diabetes and the Effect of Short-Term Intensive Insulin Treatment

TL;DR: No significant differences in the glycation of proteins between the obese and lean groups were noted, but type 2 diabetic patients had several proteins with higher glycation than the control groups, and the potential for monitoring short-term glycemic control in diabetic patients is offered.
Journal ArticleDOI

Result‐driven strategies for protein identification and quantitation – a way to optimize experimental design and derive reliable results

TL;DR: This work has shown that the off‐line coupling of μLC with MS quantitation and MS/MS identification methods makes new result‐dependent workflows possible and requires the development of innovative algorithms for these three result‐ dependent workflows that make MS andMS/MS analysis more efficient and also add confidence to experimental results.