title: Supervised multivariate analysis of sequence groups to identify specificity determining residues.
abstract: BACKGROUND
  Proteins that evolve from a common ancestor can change functionality over time, and it is important to be able identify residues that cause this change. In this paper we show how a supervised multivariate statistical method, Between Group Analysis (BGA), can be used to identify these residues from families of proteins with different substrate specifities using multiple sequence alignments.
  
  
  RESULTS
  We demonstrate the usefulness of this method on three different test cases. Two of these test cases, the Lactate/Malate dehydrogenase family and Nucleotidyl Cyclases, consist of two functional groups. The other family, Serine Proteases consists of three groups. BGA was used to analyse and visualise these three families using two different encoding schemes for the amino acids.
  
  
  CONCLUSIONS
  This overall combination of methods in this paper is powerful and flexible while being computationally very fast and simple. BGA is especially useful because it can be used to analyse any number of functional classes. In the examples we used in this paper, we have only used 2 or 3 classes for demonstration purposes but any number can be used and visualised.
authors: The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland. iain.wallace@ucd.ie
authors: Iain M
authors: IM
authors: Wallace
authors: Desmond G
authors: DG
authors: Higgins
mesh_terms: D000595:Amino Acid Sequence / Q000235:genetics*; D001483:Base Sequence / Q000235:genetics; D015999:Multivariate Analysis; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods* / Q000706:statistics & numerical data; D020539:Sequence Analysis, Protein / Q000379:methods / Q000706:statistics & numerical data; D012984:Software / Q000706:statistics & numerical data