| Algorithm |
Types |
Reference |
| Agglomerative HCT |
Investigate any correlation among discriminator genes in hereditary breast cancer |
[11] |
| E-cast |
Uses a dynamic threshold |
[12] |
| Non-HCT (CAST) |
Clustering gene expression patterns. |
[13] |
| Bayesian Biclustering |
Searches for local patterns of gene expression |
[14] |
| FABIA |
Accounts for linear dependencies between gene expression and conditions |
[15] |
| QUBIC |
Combination of qualitative measures of gene expression data and a combinatorial optimization technique |
[16] |
| CPB |
A comparative analysis of biclustering algorithms for gene expression data |
[17] |
| Combinatorial Clustering |
Three classification techniques comparison, k-NN,SVM and AdaBoost |
[18] |
| Worst-Case |
Worst-Case Analysis of Selective Sampling for Linear Classification |
[19] |
| COALESCE |
Co-regulated and sequence-level regulatory motifs |
[20] |
| Cheng and Church |
Biclustering of expression data |
[21] |
| Plaid |
A tool for exploratory analysis of multivariate data |
[22] |
| BiMax |
Sharing compatible expression patterns across subsets of samples |
[23] |
| xMOTIFs |
A conserved gene expression motif |
[24] |
| OPSM |
Capturing the general tendency of gene expressions across a subset of conditions |
[25] |
| Spectral MEQPSO |
Global convergence towards an optimal solution |
[26] |
| ISA |
Overlapping transcription modules |
[27] |
