title: CLUM: a cluster program for analyzing microarray data.
abstract: Microarray technology is increasingly being applied in biological and medical research to address a wide range of problems. Cluster analysis has proven to be a very useful tool for investigating the structure of microarray data. This paper presents a program for clustering microarray data, which is based on the so call path-distance. The algorithm gives in each step a partition in two clusters and no prior assumptions on the structure of clusters are required. It assigns each object (gene or sample) to only one cluster and gives the global optimum for the function that quantifies the adequacy of a given partition of the sample into k clusters. The program was tested on experimental data sets, showing the robustness of the algorithm.
authors.affiliation: Departamento de Ciencias de la Computación e Inteligencia Artificial, Euskal Herriko Unibertsitatea, Spain.
authors.forename: I
authors.initials: I
authors.lastname: Irigoien
authors.forename: E
authors.initials: E
authors.lastname: Fernandez
authors.forename: S
authors.initials: S
authors.lastname: Vives
authors.forename: C
authors.initials: C
authors.lastname: Arenas
mesh_terms: D000465:Algorithms; D000818:Animals; D017173:Caenorhabditis elegans / Q000235:genetics / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000502:physiology*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software