A Combinatorial Framework for Designing (Pseudoknotted) RNA Algorithms

We extend an hypergraph representation, introduced by Finkelstein and Roytberg, to unify dynamic programming algorithms in the context of RNA folding with pseudoknots. Classic applications of RNA dynamic programming energy minimization, partition function, base-pair probabilities...) are reformulated within this framework, giving rise to very simple algorithms. This reformulation allows one to conceptually detach the conformation space/energy model -- captured by the hypergraph model -- from the specific application, assuming unambiguity of the decomposition. To ensure the latter property, we propose a new combinatorial methodology based on generating functions. We extend the set of generic applications by proposing an exact algorithm for extracting generalized moments in weighted distribution, generalizing a prior contribution by Miklos and al. Finally, we illustrate our full-fledged programme on three exemplary conformation spaces (secondary structures, Akutsu's simple type pseudoknots and kissing hairpins). This readily gives sets of algorithms that are either novel or have complexity comparable to classic implementations for minimization and Boltzmann ensemble applications of dynamic programming

Internet of Things in Water Management and Treatment

The goal of the water security IoT chapter is to present a comprehensive and integrated IoT based approach to environmental quality and monitoring by generating new knowledge and innovative approaches that focus on sustainable resource management. Mainly, this chapter focuses on IoT applications in wastewater and stormwater, and the human and environmental consequences of water contaminants and their treatment. The IoT applications using sensors for sewer and stormwater monitoring across networked landscapes, water quality assessment, treatment, and sustainable management are introduced. The studies of rate limitations in biophysical and geochemical processes that support the ecosystem services related to water quality are presented. The applications of IoT solutions based on these discoveries are also discussed

ncRNA-Class Web Tool: Non-coding RNA Feature Extraction and Pre-miRNA Classification Web Tool

Part 8: First Workshop on Algorithms for Data and Text Mining in Bioinformatics (WADTMB 2012)International audienceUntil recently, it was commonly accepted that most genetic information is transacted by proteins. Recent evidence suggests that the majority of the genomes of mammals and other complex organisms are in fact transcribed into non-coding RNAs (ncRNAs), many of which are alternatively spliced and/or processed into smaller products. Non coding RNA genes analysis requires the calculation of several sequential, thermodynamical and structural features. Many independent tools have already been developed for the efficient calculation of such features but to the best of our knowledge there does not exist any integrative approach for this task. The most significant amount of existing work is related to the miRNA class of non-coding RNAs. MicroRNAs (miRNAs) are small non-coding RNAs that play a significant role in gene regulation and their prediction is a challenging bioinformatics problem. Non-coding RNA feature extraction and pre-miRNA classification Web Tool (ncRNA-class Web Tool) is a publicly available web tool (http://150.140.142.24:82/Default.aspx) which provides a user friendly and efficient environment for the effective calculation of a set of 58 sequential, thermodynamical and structural features of non-coding RNAs, plus a tool for the accurate prediction of miRNAs

Expression of Anthocyanins in Callus Cultures of Cranberry (\u3ci\u3eVaccinium macrocarpon Ait\u3c/i\u3e)

Expression of anthocyanins and other flavonoids in callus cultures established from different parts of cranberry plant was investigated and the effect of explant source on the in vitro product was determined. Callus cultures were initiated from different parts of the plant in a modified Gamborg\u27s medium with 5.37 μM α-naphthaleneacetic acid, 0.45 μM 2,4-dichlorophenoxyacetic acid, and 2.32 μM kinetin in the dark at 25°C. Callus cultures accumulated anthocyanins only on exposure to light and maximum concentration was observed by day 12. The cultures had lower levels of anthocyanins and only cyanidin 3-galactoside, cyanidin 3-glucoside, and cyanidin 3-arabinoside were identified in all cultures regardless of source of explant. Proanthocyanidin accumulation in cultures was independent of light, and levels were higher than in mature fruit. Exposure to light induced accumulation of flavonols and enhanced activity of phenylalanine ammonia-lyase in the cultures

Faster Algorithms for RNA-folding using the Four-Russians method

The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n 3) time using dynamic programming. Four-Russians is a technique that will reduce the running time for certain dynamic programming algorithms by a factor after a preprocessing step where solutions to all smaller subproblems of a fixed size are exhaustively enumerated. Frid and Gusfield designed an O ( n3) algorithm for RNA folding using the Four-Russians technique. However, in their log n algorithm the preprocessing is interleaved with the algorithm computation. We simplify the algorithm and the analysis by doing the preprocessing once prior to the algorithm computation. We call this the two-vector method. We also show variants where instead of exhaustive preprocessing, we only solve the subproblems encountered in the main algorithm once and memoize the results. We give a proof of correctness and explore the practical advantages over the earlier method. The Nussinov algorithm admits an O(n 2) parallel algorithm. We show an parallel algorithm using the two-vector idea that improves the time bound to O(n 2 / log n). We have implemented the parallel algorithm on Graphical processing units using CUDA platform. We discuss the organization of the data structures to exploit coalesced memory access for fast running time. These ideas also help in improving the running time of the serial algorithms. For sequences of up to 6000 bases the parallel algorithm takes only about 2 secs, the two-vector and memoized versions are faster than the Frid-Gusfield algorithm by a factor of 3, and faster than Nussinov by a factor of 20.