设计（伪纽结）RNA算法的组合框架
A Combinatorial Framework for Designing (Pseudoknotted) RNA Algorithms
摘要：
我们扩展了超图表示，介绍了Finkelstein和Roytberg，统一的动态规划算法的上下文中的RNA折叠与伪结。RNA动态规划能量最小化、配分函数、碱基对概率的经典应用.）在这个框架内重新制定，产生了非常简单的算法。这种重新表述允许人们从概念上分离构象空间/能量模型-由超图模型捕获-从特定的应用中，假设分解的明确性。为了确保后者的属性，我们提出了一个新的组合方法的基础上生成函数。我们提出了一个精确的算法提取广义矩的加权分布，概括了先前的贡献Miklos和人。最后，我们说明了我们的成熟的程序上的三个示例性的构象空间（二级结构，Akutsu的简单类型的伪结和接吻发夹）的通用应用程序。这很容易给出一组算法，这些算法要么是新颖的，要么具有与动态规划的最小化和玻尔兹曼集成应用的经典实现相当的复杂性。
英文摘要：
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.
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