Detecting atypical examples of known domain types by sequence similarity searching: The SBASE domain library approach

Somdutta Dhir, Mircea Pacurar, Dino Franklin, Zoltán Gáspári, Attila Kertész-Farkas, András Kocsor, Frank Eisenhaber, Sándor Pongor

Research output: Article

6 Citations (Scopus)

Abstract

SBASE is a project initiated to detect known domain types and predicting domain architectures using sequence similarity searching (Simon et al., Protein Seq Data Anal, 5: 39-42, 1992, Pongor et al., Nucl. Acids. Res. 21:3111-3115, 1992). The current approach uses a curated collection of domain sequences - the SBASE domain library - and standard similarity search algorithms, followed by postprocessing which is based on a simple statistics of the domain similarity network (http://hydra.icgeb.trieste.it/sbase/). It is especially useful in detecting rare, atypical examples of known domain types which are sometimes missed even by more sophisticated methodologies. This approach does not require multiple alignment or machine learning techniques, and can be a useful complement to other domain detection methodologies. This article gives an overview of the project history as well as of the concepts and principles developed within this the project.

Original languageEnglish
Pages (from-to)538-549
Number of pages12
JournalCurrent Protein and Peptide Science
Volume11
Issue number7
DOIs
Publication statusPublished - dec. 1 2010

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Cell Biology

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