title: APTANI: a computational tool to select aptamers through sequence-structure motif analysis of HT-SELEX data.
abstract: BACKGROUND
  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.
  
  
  METHODS
  APTANI is available at http://aptani.unimore.it.
  
  
  BACKGROUND
  silvio.bicciato@unimore.it
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Center for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy and.
authors.forename: J
authors.initials: J
authors.lastname: Caroli
authors.affiliation: Center for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy and.
authors.forename: C
authors.initials: C
authors.lastname: Taccioli
authors.affiliation: Department of Microbiology & Immunology, UM/Sylvester Comprehensive Cancer Center, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
authors.forename: A
authors.initials: A
authors.lastname: De La Fuente
authors.affiliation: Department of Microbiology & Immunology, UM/Sylvester Comprehensive Cancer Center, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
authors.forename: P
authors.initials: P
authors.lastname: Serafini
authors.affiliation: Center for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy and.
authors.forename: S
authors.initials: S
authors.lastname: Bicciato
mesh_terms: D000465:Algorithms; D052157:Aptamers, Nucleotide / Q000737:chemistry*; D059014:High-Throughput Nucleotide Sequencing; D059372:Nucleotide Motifs; D052156:SELEX Aptamer Technique / Q000379:methods*; D012984:Software
chemical_list: D052157:Aptamers, Nucleotide