title: A robust clustering approach for NMR spectra of natural product extracts.
abstract: A robust method was developed to cluster similar NMR spectra from partially purified extracts obtained from a range of marine sponges and a plant biota. The NMR data were acquired using microtiter plate NMR (VAST) in protonated solvents. A sample data set which contained several clusters was used to optimize the protocol. The evaluation of the robustness was performed using three different clustering methods: tree clustering analysis, K-means clustering and multidimensional scaling. These methods were compared for consistency using the sample data set and the optimized methodology was applied to clustering of a set of spectra from partially purified biota extracts.
authors.affiliation: Natural Product Discovery, Eskitis Institute, Griffith University, Brisbane, Queensland 4111, Australia.
authors.forename: Gregory K
authors.initials: GK
authors.lastname: Pierens
authors.forename: Meredith E
authors.initials: ME
authors.lastname: Palframan
authors.forename: Carolyn J
authors.initials: CJ
authors.lastname: Tranter
authors.forename: Anthony R
authors.initials: AR
authors.lastname: Carroll
authors.forename: Ronald J
authors.initials: RJ
authors.lastname: Quinn
mesh_terms: D000818:Animals; D044822:Biodiversity; D001685:Biological Factors / Q000737:chemistry*; D016000:Cluster Analysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D011161:Porifera / Q000737:chemistry*
chemical_list: D001685:Biological Factors