Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps.
Peter MeinickeThomas LingnerAlexander KaeverKirstin FeussnerCornelia GöbelIvo FeussnerPetr KarlovskyBurkhard MorgensternPublished in: Algorithms Mol. Biol. (2008)
Keyphrases
- self organizing maps
- mass spectrometry data
- mass spectrometry
- neural network
- neural gas
- k means
- unsupervised learning
- high throughput
- visualization methods
- pattern classification
- input data
- som neural network
- clustering method
- generative topographic mapping
- gene expression profiles
- image data
- data clustering
- cancer classification
- computational biology
- active learning
- clustering algorithm