Computational cluster validation in post-genomic data analysis

By Julia Handl, Joshua D. Knowles, Douglas B. Kell. Bioinform., 2005

988 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/233954b16bfce5fabf9d1e160f6fdf3c4dcb92a5

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Citations in the corpus

Performance metrics in multi-objective optimization (2015, background): “42 Spread: Generalized Spread [43] Δ∗ 43 Success Counting [44] SCC 44 Sum of maximum objective values [45] Smax 45 The adjusted Rand Index [46] 46 The average distance of points to the PF [47] 47 The delineation metric [48] 48 The diversity metric [48] 49 The front Spread [49] FS 50 The front to Set”
Visualizing Assumptions and Results in Network Meta-analysis: The Network Graphs Package (2015, methodology): “…absolute-value distance, etc.) and linkage method (single, average, weighted, complete, ward, centroid, median) based on the cophenetic correlation coeﬃcient, which measures how faithfully the output dendrogram represents the dissimilarities between observations (Handl, Knowles, and Kell 2005).”
FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data (2007, background): “Though in some particular cases they perform better than standard methods, none of them proved consistently better across multiple different datasets (reviewed in [4]).”
Defining functional areas in individual human brains using resting functional connectivity MRI (2008, methodology): “The commonly chosen UPGMA (Unweighted Paired GroupMethod with Arithmetic mean) hierarchical clustering method (Eisen et al., 1998; Handl et al., 2005) sorted the eta(2) profiles for each seed's correlationmap into three main groups (Fig.”
Expectation and purpose: understanding users' mental models of mobile app privacy through crowdsourcing (2012, background): “The other criteria is the combination of three internal measures, namely connectivity [64], Silhouette Width [65] and Dunn Index [66].”
An Evolutionary Approach to Multiobjective Clustering (2007, methodology): “criterion (implicitly or explicitly) optimized by the algorithm [8].”
Ant-based and swarm-based clustering (2007, background): “Similarly, a wide range of different objective functions can be derived from a large variety of different clustering quality measures (Handl et al. 2005).”
Modeling Users' Mobile App Privacy Preferences: Restoring Usability in a Sea of Permission Settings (2014, background): “The other criteria is the combination of three internal measures, namely connectivity [64], Silhouette Width [65] and Dunn Index [66].”
Proposed minimum reporting standards for data analysis in metabolomics (2007, background): “A recent reviewed describes the different approaches available (Handl et al. 2005).”
Is My Network Module Preserved and Reproducible? (2011, background): “Cluster validation measures and approaches are reviewed in [52].”
A Survey of Clustering Ensemble Algorithms (2011, methodology): “However, these analyses were motivated by an interest in ̄nding the best external cluster validity index.(41) Therefore, the properties of these measures are not studied from the perspective of how they can be suitable for the median”
How does gene expression clustering work? (2005, background): “…versus between-group variance, the separation between clusters and the stability of clusters with respect to noise, random initializations (such as for k -means or SOM) and leaving out conditions for example (see Handl et al. 7 for an overview of internal validation measures and their biases).”
Statistical Significance of Clustering for High-Dimension, Low–Sample Size Data (2008, background): “Some case studies on validation of clusters have been given by Azuaje (2002) and Handl, Knowles, and Kell (2005).”