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Isothermal nucleic acid amplification is becoming increasingly important for molecular diagnostics. Therefore, new computational tools are needed to facilitate assay design. In the isothermal EXPonential Amplification Reaction (EXPAR), template sequences with similar thermodynamic characteristics perform very differently. To understand what causes this variability, we characterized the performance of 384 template sequences, and used this data to develop two computational methods to predict EXPAR template performance based on sequence: a position weight matrix approach with support vector machine classifier, and RELIEF attribute evaluation with Nave Bayes classification. The methods identified well and poorly performing EXPAR templates with 6770 sensitivity and 7780 specificity. We combined these methods into a computational tool that can accelerate new assay design by ruling out likely poor performers. Furthermore, our data suggest that variability in template performance is linked to specific sequence motifs. Cytidine, a pyrimidine base, is over-represented in certain positions of well-performing templates. Guanosine and adenosine, both purine bases, are over-represented in similar regions of poorly performing templates, frequently as GA or AG dimers. Since polymerases have a higher affinity for purine oligonucleotides, polymerase binding to GA-rich regions of a single-stranded DNA template may promote non-specific amplification in EXPAR and other nucleic acid amplification reactions. © 2012 The Author(s).