Carbon fiber microelectrodes modified with molecularly imprinted polymers for selective peptide detection
Abstract
With the increasing size of proteomics data sets, there is an emerging need for reliable methods of monitoring LC-MS instrument performance over time to ensure consistency in the data. In this poster, I present a quality control protocol for assessing variation within LC-MS data. The software Skyline is used to extract three analytical figures of merit from bovine serum albumin (BSA) chromatograms. These figures are compared longitudinally to monitor changes in instrument performance over time. I also use the protocol to compare two different types of LC columns used in our facility, homemade and commercial, to determine which yields superior data.
Primary Faculty Mentor Name
Yangguang Ou
Status
Undergraduate
Student College
College of Arts and Sciences
Program/Major
Biochemistry
Primary Research Category
Physical Science
Carbon fiber microelectrodes modified with molecularly imprinted polymers for selective peptide detection
With the increasing size of proteomics data sets, there is an emerging need for reliable methods of monitoring LC-MS instrument performance over time to ensure consistency in the data. In this poster, I present a quality control protocol for assessing variation within LC-MS data. The software Skyline is used to extract three analytical figures of merit from bovine serum albumin (BSA) chromatograms. These figures are compared longitudinally to monitor changes in instrument performance over time. I also use the protocol to compare two different types of LC columns used in our facility, homemade and commercial, to determine which yields superior data.
