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Teiresias is a fast, exhaustive pattern discovery algorithm. It can be used on any alphabet, but its primary application has been DNA and amino acid sequences. The core algorithm has been used to implement motif discovery, multiple alignment, automatic protein annotation and other tools. It is named after Tiresias, the blind prophet in Greek mythology.

It was developed by Isidore Rigoutsos and Aris Floratos at IBM Healthcare and life sciences in the Bioinformatics and Pattern Discovery Group, Computational Biology Center, Deep Computing Institute, IBM TJ Watson Research Center.

It is available for online use or can be downloaded.


  1. Rigoutsos I and Floratos A. Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm. Bioinformatics. 1998;14(1):55-67. PubMed ID:9520502 | HubMed [1]
  2. Parida L, Floratos A, and Rigoutsos I I. MUSCA: An Algorithm for Constrained Alignment of Multiple Data Sequences. Genome Inform Ser Workshop Genome Inform. 1998;9:112-119. PubMed ID:11072327 | HubMed [2]
  3. Rigoutsos I, Floratos A, Ouzounis C, Gao Y, and Parida L. Dictionary building via unsupervised hierarchical motif discovery in the sequence space of natural proteins. Proteins. 1999 Nov 1;37(2):264-77. PubMed ID:10584071 | HubMed [3]
  4. Rigoutsos I, Gao Y, Floratos A, and Parida L. Building dictionaries of 1D and 3D motifs by mining the Unaligned 1D sequences of 17 archaeal and bacterial genomes. Proc Int Conf Intell Syst Mol Biol. 1999:223-33. PubMed ID:10786305 | HubMed [4]
  5. Rigoutsos I, Huynh T, Floratos A, Parida L, and Platt D. Dictionary-driven protein annotation. Nucleic Acids Res. 2002 Sep 1;30(17):3901-16. PubMed ID:12202776 | HubMed [5]
  6. Jensen KL, Styczynski MP, Rigoutsos I, and Stephanopoulos GN. A generic motif discovery algorithm for sequential data. Bioinformatics. 2006 Jan 1;22(1):21-8. DOI:10.1093/bioinformatics/bti745 | PubMed ID:16257985 | HubMed [6]
All Medline abstracts: PubMed | HubMed
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