Efficient Pattern Matching in Python

Pattern matching is a powerful tool for symbolic computations. Applications include term rewriting systems, as well as the manipulation of symbolic expressions, abstract syntax trees, and XML and JSON data. It also allows for an intuitive description of algorithms in the form of rewrite rules. We present the open source Python module MatchPy, which offers functionality and expressiveness similar to the pattern matching in Mathematica. In particular, it includes syntactic pattern matching, as well as matching for commutative and/or associative functions, sequence variables, and matching with constraints. MatchPy uses new and improved algorithms to efficiently find matches for large pattern sets by exploiting similarities between patterns. The performance of MatchPy is investigated on several real-world problems

Reduced mRNA Secondary-Structure Stability Near the Start Codon Indicates Functional Genes in Prokaryotes

Several recent studies have found that selection acts on synonymous mutations at the beginning of genes to reduce mRNA secondary-structure stability, presumably to aid in translation initiation. This observation suggests that a metric of relative mRNA secondary-structure stability, ZΔG, could be used to test whether putative genes are likely to be functionally important. Using the Escherichia coli genome, we compared the mean ZΔG of genes with known functions, genes with known orthologs, genes where function and orthology are unknown, and pseudogenes. Genes in the first two categories demonstrated similar levels of selection for reduced stability (increased ZΔG), whereas for pseudogenes stability did not differ from our null expectation. Surprisingly, genes where function and orthology were unknown were also not different from the null expectation, suggesting that many of these open reading frames are not functionally important. We extended our analysis by constructing a Bayesian phylogenetic mixed model based on data from 145 prokaryotic genomes. As in E. coli, genes with no known function had consistently lower ZΔG, even though we expect that many of the currently unannotated genes will ultimately have their functional utility discovered. Our findings suggest that functional genes tend to evolve increased ZΔG, whereas nonfunctional ones do not. Therefore, ZΔG may be a useful metric for identifying genes of potentially important function and could be used to target genes for further functional study

A specification-to-deployment architecture for overlay networks

Implementing overlay software is non-trivial and time-consuming. Current projects build overlays or intermediate frameworks on top of low-level networking abstractions. This leads to far reaching incompatibilities between overlay implementations, tight coupling to frameworks and limited adaptability to different deployment environments. We present a new approach to rapid overlay implementation that combines a modelling framework for overlay design with a dynamic component architecture for run-time adaptation. It is the first architecture in the overlay area that tackles the complete design process from modelling, through code generation and implementation down to adaptive deployment. To demonstrate the effectiveness of this architecture, we describe the step-by-step procedure of designing an overlay and deploying it within an adaptive middleware framework