title: Remote homology detection based on oligomer distances.
abstract: BACKGROUND
  Remote homology detection is among the most intensively researched problems in bioinformatics. Currently discriminative approaches, especially kernel-based methods, provide the most accurate results. However, kernel methods also show several drawbacks: in many cases prediction of new sequences is computationally expensive, often kernels lack an interpretable model for analysis of characteristic sequence features, and finally most approaches make use of so-called hyperparameters which complicate the application of methods across different datasets.
  
  
  RESULTS
  We introduce a feature vector representation for protein sequences based on distances between short oligomers. The corresponding feature space arises from distance histograms for any possible pair of K-mers. Our distance-based approach shows important advantages in terms of computational speed while on common test data the prediction performance is highly competitive with state-of-the-art methods for protein remote homology detection. Furthermore the learnt model can easily be analyzed in terms of discriminative features and in contrast to other methods our representation does not require any tuning of kernel hyperparameters.
  
  
  BACKGROUND
  Normalized kernel matrices for the experimental setup can be downloaded at www.gobics.de/thomas. Matlab code for computing the kernel matrices is available upon request.
  
  
  BACKGROUND
  thomas@gobics.de, peter@gobics.de.
authors.affiliation: Abteilung Bioinformatik, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen Goldschmidtstr. 1, 37077 Göttingen, Germany. thomas@gobics.de
authors.forename: Thomas
authors.initials: T
authors.lastname: Lingner
authors.forename: Peter
authors.initials: P
authors.lastname: Meinicke
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D019281:Dimerization; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid
chemical_list: D011506:Proteins