title: AMIC@: All MIcroarray Clusterings @ once.
abstract: The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica.
authors.affiliation: Istituto di Informatica e Telematica del C.N.R., Via Moruzzi 1, Pisa, Italy.
authors.forename: Filippo
authors.initials: F
authors.lastname: Geraci
authors.forename: Marco
authors.initials: M
authors.lastname: Pellegrini
authors.forename: M Elena
authors.initials: ME
authors.lastname: Renda
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003196:Computer Graphics; D020869:Gene Expression Profiling / Q000379:methods*; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software