Data analysis

The Story

This category of my research begins with the analysis of how instruments convert the quantity to be measured into a number. The development of the concept of data domains helps follow the ways in which data is encoded in instrumentation, and the devices that convert from one form of encoding to another.

During the development of applications for tandem mass spectrometry, I worked on automating the identification of the selected ion from its fragment spectra. We attempted to do this heuristically, but these days, one would give the problem to an AI program.

There are several papers on improving the efficiency or power of analytical techniques through computer automation. The most often cited papers are Tim Nieman’s on polynomial smoothing for signal-to-noise enhancement (a graph from which is shown in the illustration for this category), Mark LaPack’s on relating membrane permeability to Hildebrand solubility factors, and Jae Schwartz’s on the scan modes in tandem mass spectrometry. This latter work done in collaboration with Graham Cooks.

Publications in Data Analysis

Collaborators in this work were Timothy Nieman, George Leroi, Edward Darland, James Holler, Stanley Crouch, Kevin Cross, Peter Palmer, Carl Beckner, Ann Giordani, Hugh Gregg, Phillip Hoffman, Adrian Wade, Kent Voorhees, Stephen Durfee, James Holtzclaw, Mark Bauer, Jae Schwartz, R. Graham Cooks, Brian Eckenrode, Jack Watson, John Holland, Bobbette Nourse, D. L. Diedrich, Mark Cole, Stephen Chan, Mark LaPack, Victoria McGuffin, J.C. Tou, Ronald Lopshire, and Fei Overney.

Previous

Chemical Instrumentation
Next

Spectroscopy & Chromatography