APTANI: A computational tool to select aptamers through sequence-structure motif analysis of HT-SELEX data

J. Caroli, C. Taccioli, A. De La Fuente, P. Serafini, S. Bicciato

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Motivation: Aptamers are synthetic nucleic acid molecules that can bind biological targets in virtue of both their sequence and three-dimensional structure. Aptamers are selected using SELEX, Systematic Evolution of Ligands by EXponential enrichment, a technique that exploits aptamer-target binding affinity. The SELEX procedure, coupled with high-throughput sequencing (HT-SELEX), creates billions of random sequences capable of binding different epitopes on specific targets. Since this technique produces enormous amounts of data, computational analysis represents a critical step to screen and select the most biologically relevant sequences. Results: Here, we present APTANI, a computational tool to identify target-specific aptamers from HT-SELEX data and secondary structure information. APTANI builds on AptaMotif algorithm, originally implemented to analyze SELEX data; extends the applicability of AptaMotif to HT-SELEX data and introduces new functionalities, as the possibility to identify binding motifs, to cluster aptamer families or to compare output results from different HT-SELEX cycles. Tabular and graphical representations facilitate the downstream biological interpretation of results. Availability and implementation: APTANI is available at http://aptani.unimore.it. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)161-164
Number of pages4
Issue number2
StatePublished - Jan 15 2016

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


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