Maximizing chemical knowledge: New approaches in spectral data mining and search via the successful consolidation of multi-technique spectral data

CINF 18

Gregory M. Banik, gregory_banik@bio-rad.com1, Deborah Kernan, deborah_kernan@bio-rad.com2, Kevin Scully, kevin_scully@bio-rad.com3, and Marie Scandone, marie_scandone@bio-rad.com1. (1) Informatics Division, Bio-Rad Laboratories, TWO PENN CENTER PLAZA, SUITE 800, 1500 JFK Blvd., Philadelphia, PA 19102, (2) Bio-Rad Laboratories, Informatics Division, 3316 Spring Garden, Phila, PA 19104, (3) Bio-Rad Laboratories, Informatics Division, 3316 Spring Garden Street, Philadelphia, PA 19104
It has become standard practice in multiple applications, such as compound verification or unknown sample identification, for scientists to run a sample and, using spectral search software, compare it to commercial and/or proprietary reference databases of spectra. The software mines the reference data and calculates a score or hit quality index (HQI) to describe the correlation or “closeness” of the match between the spectrum being examined and the spectra of known compounds in reference databases.

This paper describes a new approach to spectral searching which gives scientists who analyze samples using multiple spectral techniques the ability to simultaneously combine all spectral information available to yield a single search result. In a series of case studies, we will demonstrate how this approach enables the optimization of chemical similarity and maximizes chemical knowledge in order to identify several unknown samples.

 

Advances in Data-mining and Analysis: Informatics Perspective
8:00 AM-11:00 AM, Monday, 29 August 2005 Washington DC Convention Center -- 151B, Oral

Division of Chemical Information

The 230th ACS National Meeting, in Washington, DC, Aug 28-Sept 1, 2005