The search for novel proteins is complicated by the diversity of amino acids, the non-linear relationship between amino acid sequence and folding and the huge size of sequence space. The goal of this research is to discover patterns in amino acid composition and sequence that relate to known or novel folds, thereby helping to constrain the search space for new functional proteins. This approach...

In the bioinformatics literature, pairwise sequence alignment methods appear with many variations and diverse applications. With this abundance, comes not only an emphasis on speed and memory efficiency, but also a need for assigning confidence to the computed alignments through p-value estimation, especially for important segment pairs within an alignment. This paper examines an empirical tech...

A pseudo-random number generator (RNG) might be used to generate w-bit random samples in d dimensions if the number of state bits is at least dw. Some RNGs perform better than others and the concept of equidistribution has been introduced in the literature in order to rank different RNGs. We define what it means for a RNG to be (d,w)-equidistributed, and then argue that (d,w)-equidistribution i...

Protein sequence alignmentmay be viewed as either a classification or amultiple hypothesis testing problem.Whereas the type one error of a method is often studied for randomly generated sequences, the power is best investigated based on real protein sequences. The SCOP data base and its protein classification is used to investigate both the power and the type one error of sequence alignment as ...

Small non-coding RNAs (sRNAs) are regulatory RNA molecules that have been identified in a multitude of bacterial species and shown to control numerous cellular processes through various regulatory mechanisms. In the last decade, next generation RNA sequencing (RNA-seq) has been used for the genome-wide detection of bacterial sRNAs. Here we describe sRNA-Detect, a novel approach to identify expr...

Recurrent Neural Networks (RNNs) — particularly Long Short Term Memory (LSTM) RNNs — are a popular and very successful model for generating sequences. However, most LSTM based sequence generation techniques are currently not interactive and do not allow continuous control of the sequence generation, let alone in a gestural or expressive manner. This research investigates methods of realtime con...