title: Analysis of expression profile using fuzzy adaptive resonance theory.
abstract: BACKGROUND
  It is well understood that the successful clustering of expression profiles give beneficial ideas to understand the functions of uncharacterized genes. In order to realize such a successful clustering, we investigate a clustering method based on adaptive resonance theory (ART) in this report.
  
  
  RESULTS
  We apply Fuzzy ART as a clustering method for analyzing the time series expression data during sporulation of Saccharomyces cerevisiae. The clustering result by Fuzzy ART was compared with those by other clustering methods such as hierarchical clustering, k-means algorithm and self-organizing maps (SOMs). In terms of the mathematical validations, Fuzzy ART achieved the most reasonable clustering. We also verified the robustness of Fuzzy ART using noised data. Furthermore, we defined the correctness ratio of clustering, which is based on genes whose temporal expressions are characterized biologically. Using this definition, it was proved that the clustering ability of Fuzzy ART was superior to other clustering methods such as hierarchical clustering, k-means algorithm and SOMs. Finally, we validate the clustering results by Fuzzy ART in terms of biological functions and evidence.
  
  
  BACKGROUND
  The software is available at http//www.nubio.nagoya-u.ac.jp/proc/index.html
authors.affiliation: Department of Biotechnology, School of Engineering Nagoya University, Furo-cho, Chikusa-ku, Japan.
authors.forename: Shuta
authors.initials: S
authors.lastname: Tomida
authors.forename: Taizo
authors.initials: T
authors.lastname: Hanai
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Honda
authors.forename: Takeshi
authors.initials: T
authors.lastname: Kobayashi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D030541:Databases, Genetic; D017143:Fuzzy Logic; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods* / Q000706:statistics & numerical data*; D005786:Gene Expression Regulation; D008957:Models, Genetic; D015233:Models, Statistical; D012333:RNA, Messenger / Q000032:analysis / Q000737:chemistry / Q000235:genetics; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000502:physiology; D012680:Sensitivity and Specificity; D013172:Spores, Fungal; D013269:Stochastic Processes; D013997:Time Factors
chemical_list: D012333:RNA, Messenger