A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection.
Oliver M. CrookAikaterini GeladakiDaniel J. H. NightingaleOwen L. VennardKathryn S. LilleyLaurent GattoPaul D. W. KirkPublished in: PLoS Comput. Biol. (2020)
Keyphrases
- novelty detection
- semi supervised
- cellular processes
- semi supervised learning
- text filtering
- signal transduction
- labeled data
- amino acids
- anomaly detection
- experimental conditions
- unlabeled data
- protein sequences
- protein structure
- unsupervised learning
- protein protein interactions
- pairwise
- concept drift
- biological systems
- supervised learning
- active learning
- support vector data description
- data mining
- data streams
- training data
- minimum volume
- database systems