title: Probabilistic alignment of motifs with sequences.
abstract: BACKGROUND
  Motif detection is an important component of the classification and annotation of protein sequences. A method for aligning motifs with an amino acid sequence is introduced. The motifs can be described by the secondary (i.e. functional, biophysical, etc.) characteristics of a signal or pattern to be detected. The results produced are based on the statistical relevance of the alignment. The method was targeted to avoid the problems (i.e. over-fitting, biological interpretation and mathematical soundness) encountered in other methods currently available.
  
  
  RESULTS
  The method was tested on lipoprotein signals in B. subtilis yielding stable results. The results of signal prediction were consistent with other methods where literature was available.
  
  
  BACKGROUND
  An implementation of the motif alignment, refining and bootstrapping is available for public use online at http://www.expasy.org/tools/patoseq/
authors.affiliation: GeneBio S.A., 25. Av. de Champel, 1206 Geneva, Switzerland. pedro.gonnet@genebio.com
authors.forename: Pedro
authors.initials: P
authors.lastname: Gonnet
authors.forename: Frédérique
authors.initials: F
authors.lastname: Lisacek
mesh_terms: D020816:Amino Acid Motifs / Q000235:genetics*; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D001412:Bacillus subtilis / Q000737:chemistry / Q000235:genetics; D030562:Databases, Protein; D005246:Feedback; D008074:Lipoproteins / Q000737:chemistry / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated; D011336:Probability; D011506:Proteins / Q000145:classification* / Q000235:genetics; D016415:Sequence Alignment / Q000379:methods* / Q000706:statistics & numerical data; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D008074:Lipoproteins; D011506:Proteins