MOTIVATION Pattern discovery algorithms are widely used for the analysis of DNA and protein sequences. Most algorithms have been designed to find overrepresented motifs in sparse datasets of long sequences, and ignore most positional information. We introduce an algorithm optimized to exploit spatial information in sparse-but-populous datasets. RESULTS Our algorithm Tree-based Weighted-Positi...

In this paper, we study the maximal pattern discovery problem in a given sequence for the class ERP of flexible patterns with applications to text mining, where a flexible pattern is a sequence of constant and wildcards for possibly empty strings such as AB*B*ABC, and also known as erasing regular patterns. We first discuss the framework of optimal pattern discovery for predictive mining and te...

We present a novel technique for combining statistical machine learning for proof-pattern recognition with symbolic methods for lemma discovery. The resulting tool, ACL2(ml), gathers proof statistics and uses statistical pattern-recognition to pre-processes data from libraries, and then suggests auxiliary lemmas in new proofs by analogy with already seen examples. This paper presents the implem...