Long non-coding RNA structure and function: Is there a link?

RNA has emerged as the prime target for diagnostics, therapeutics and the development of personalized medicine. In particular, the non-coding RNAs (ncRNAs) that do not encode proteins, display remarkable biochemical versatility. They can fold into complex structures and interact with proteins, DNA and other RNAs, modulating the activity, DNA targets or partners of multiprotein complexes. Thus, ncRNAs confer regulatory plasticity and represent a new layer of epigenetic control that is dysregulated in disease. Intriguingly, for long non-coding RNAs (lncRNAs, >200 nucleotides length) structural conservation rather than nucleotide sequence conservation seems to be crucial for maintaining their function. LncRNAs tend to acquire complex secondary and tertiary structures and their functions only impose very subtle sequence constraints. In the present review we will discuss the biochemical assays that can be employed to determine the lncRNA structural configurations. The implications and challenges of linking function and lncRNA structure to design novel RNA therapeutic approaches will also be analyzed

A Firefly-inspired method for protein structure prediction in lattice models

We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa–Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function valuations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models

Crispr/Cas9 gene editing reveals novel tertiary constraints in clustered mirna processing

MicroRNAs (miRNAs) play an important role in the cellular function. They often form families, with members sharing high sequence homology, a property that hampers miRNA research as there is a lack of elegant tools for specific miRNA manipulation

Crispr/Cas9 editing reveals novel mechanisms of clustered microRNA regulation and function

MicroRNAs (miRNAs) are important regulators of diverse physiological and pathophysiological processes. MiRNA families and clusters are two key features in miRNA biology. Here we explore the use of CRISPR/Cas9 as a powerful tool to delineate the function and regulation of miRNA families and clusters. We focused on four miRNA clusters composed of miRNA members of the same family, homoclusters or different families, hetero-clusters. Our results highlight different regulatory mechanisms in miRNA cluster expression. In the case of the miR-497~195 cluster, editing of miR-195 led to a significant decrease in the expression of the other miRNA in the cluster, miR-497a. Although no gene editing was detected in the miR-497a genomic locus, computational simulation revealed alteration in the three dimensional structure of the pri miR-497~195 that may affect its processing. In cluster miR- 143~145 our results imply a feed-forward regulation, although structural changes cannot be ruled out. Furthermore, in the miR-17~92 and miR-106~25 clusters no interdependency in miRNA expression was observed. Our findings suggest that CRISPR/Cas9 is a powerful gene editing tool that can uncover novel mechanisms of clustered miRNA regulation and function

Run-time Estimates for Protein Folding Simulation--in the H-P Model

Peer reviewe

Combinatorial landscape analysis for k-SAT instances

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/CEC.2008.4631133Over the past ten years, methods from statistical physics have provided a deeper inside into the average complexity of hard combinatorial problems, culminating in a rigorous proof for the asymptotic behaviour of the k-SAT phase transition threshold by Achlioptas and Peres in 2004. On the other hand, when dealing with individual instances of hard problems, gathering information about specific properties of instances in a pre-processing phase might be helpful for an appropriate adjustment of local search-based procedures. In the present paper, we address both issues in the context of landscapes induced by k-SAT instances: Firstly, we utilize a sampling method devised by Garnier and Kallel in 2002 for approximations of the number of local maxima in landscapes generated by individual k-SAT instances and a simple neighbourhood relation. The objective function is given by the number of satisfied clauses. Secondly, we outline a method for obtaining upper bounds for the average number of local maxima in k-SAT instances which indicates some kind of phase transition for the neighbourhood-specific ratio m/n = Θ(2k/k).Final Published versio

Estimating the Number of Local Maxima for k-SAT Instances

We explore the applicability of a sampling method devised by J. Garnier and L. Kallel (SIAM J. Discrete Math., 2002) to approximate the number of local maxima in search spaces induced by k-SAT instances and a simple neighbourhood relation. The objective function is given by the number of satisfied clauses. Although the problem setting for k-SAT instances does not meet all pre-conditions required by the Garnier/Kallel-approach, we obtain approximations of the number of local maxima within the same order of magnitude as the exact values that have been determined by complete search. Since the comparison requires calculation of the complete --set of local maxima, only small k-SAT instances have --been considered so far. Furthermore, we outline a method for obtaining upper bounds for the average number of local maxima in k-SAT instances, which shows changes in the average number around the phase transition threshold.Peer reviewe

Two simulated annealing-based heuristics for the job shop scheduling problem

In this paper, we present two simulated annealing-based algorithms for the classical, general job shop scheduling problem where the objective is to minimize the makespan. We consider sets of jobs consisting of tasks and sets of machines, which can handle at most one task at a time. To represent the problem, we employ the model of disjunctive graphs. Simulated annealing has been applied to this problem earlier, e.g., by Van Laarhoven et al., where the neighborhood function is based on reversing a single arc of a longest path of the underlying graph. In our approach, we analyze a neighborhood function which involves a non-uniform generation probability. To obtain the neighbors of a schedule, we reverse more than a single arc of longest paths and perform a control on the increase of the makespan. The selection of the arcs depends on the number of longest paths to which a particular arc belongs. Furthermore, we have designed two cooling schedules which employ a detailed analysis of the objective function. Depending on the specified neighborhood relation, the expected run-times can be either O(n2+ε) or O(n3+ε/m) for the first cooling schedule and O(n5/2+ε·m1/2) or O(n7/2+ε/m1/2) for the second cooling schedule, where n is the number of tasks, m the number of machines and ε represents View the MathML source. Our computational experiments on small to large benchmark problems have shown that within short series of consecutive trials relatively stable results equal or close to optimal solutions are repeatedly obtained, including the well-known benchmark problems FT10 and LA38. We could improve five upper bounds for the YN1, YN4, SWV12, SWV13, and SWV15 benchmark problems, e.g., for SWV13 the gap between the lower and the former upper bound has been shortened by about 57%. In our approach we rely only on basic information about the given problem instance