Object Weighting: A New Clustering Approach to Deal with Outliers and Cluster Overlap in Computational Biology.
Alexandre GondeauZahia AouabedMohamed HijriPedro R. Peres-NetoVladimir MakarenkovPublished in: IEEE ACM Trans. Comput. Biol. Bioinform. (2021)
Keyphrases
- computational biology
- clustering algorithm
- similar objects
- overlapping clusters
- data points
- data objects
- hierarchical clustering
- outlier detection
- protein sequences
- data clustering
- molecular biology
- natural language processing
- cluster structure
- arbitrary shape
- machine learning
- cluster analysis
- clustering method
- clustering approaches
- cluster membership
- inter cluster
- uncertain objects
- clustering framework
- k means
- cluster centers
- unsupervised clustering
- disjoint clusters
- clustering procedure
- d objects
- intra cluster
- sequence analysis
- subspace clustering
- document clustering
- variable weighting
- string kernels
- self organizing maps
- clustering result
- hierarchical clustering algorithm
- gene expression profiling
- fuzzy clustering
- clustering quality
- data mining
- feature space
- multiple sequence alignment
- high dimensional data
- spectral clustering
- cluster validation
- protein structure prediction
- density based clustering algorithm
- homogeneous groups
- information extraction
- biological sequences
- knowledge representation